Physics Working Group

The primary physics task of STAR is to study the formation and characteristics of the quark-gluon plasma (QGP), a state of matter believed to exist at sufficiently high energy densities. Detecting and understanding the QGP allows us to understand better the universe in the moments after the Big Bang, where the symmetries (and lack of symmetries) of our surroundings were put into motion.

Unlike other physics experiments where a theoretical idea can be tested directly by a single measurement, STAR must make use of a variety of simultaneous studies in order to draw strong conclusions about the QGP. This is due both to the complexity of the system formed in the high-energy nuclear collision and the unexplored landscape of the physics we study. STAR therefore consists of several types of detectors, each specializing in detecting certain types of particles or characterizing their motion. These detectors work together in an advanced data acquisition and subsequent physics analysis that allows final statements to be made about the collision.

The physics of star can be divided into several topics, with many overlaps between topics. In STAR, each of these topics is explored within a physics working group which develops the analysis techniques and software needed to focus on its interests.

Heavy Flavor

Analysis of data related to charm and bottom production and observables in STAR.

Depending on the energy scale, there are two mechanisms that generate quark masses with different degrees of importance: current quark masses are generated by the electroweak symmetry breaking mechanism (Higgs mass) and spontaneous chiral symmetry breaking leads to the constituent quark masses in QCD (QCD mass). The QCD interaction strongly affects the light quarks (u, d, s) while the heavy quark masses (c, b, t) are mainly determined by the Higgs mechanism. In high-energy nuclear collisions at RHIC, heavy quarks are produced through gluon fusion and qq¯ annihilation. Heavy quark production is also sensitive to the parton distribution function. Unlike the light quarks, heavy quark masses are not modified by the surrounding QCD medium (or the excitations of the QCD medium) and the value of their masses is much higher than the initial excitation of the system. It is these differences between light and heavy quarks in a medium that make heavy quarks an ideal probe to study the properties of the hot and dense medium created in high-energy nuclear collisions.

 

Heavy flavor analyses at STAR can be separated into quarkonia, open heavy flavor and heavy flavor leptons.


 

Abstracts, Presentations and Proceedings

Abstracts

This page is maintained by Gang Wang.

 

#9995# DNP (fall meeting) 2010

 Abstracts for DNP (fall meeting) 2010 (Nov. 2-6, 2010, Santa Fe, NM)

  • Wenqin Xu

Title: Extracting bottom quark production cross section from p+p collisions at RHIC

 

The STAR collaboration has measured the non-photonic electron (NPE) production at high transverse momentum (pT ) at middle rapidity in p + p collisions at sqrt(s) = 200 GeV at the Relativistic Heavy Ion Collider (RHIC). The relative contributions  of bottom and charm hadrons to NPE have also been obtained through electron hadron azimuthal 
correlation studies. Combining these two,  we are able to determine the high pT mid-rapidity electron spectra 
from bottom and charm decays, separately.

PYTHIA with different tunes and FONLL calculations have been compared  with this measured electron spectrum
from bottom decays to extract the bb-bar differential cross section after normalization to the measured spectrum.
The extrapolation of the total bb-bar production cross section in the whole kinematic range and its dependence
on spectrum shapes from model calculations will also be discussed.

 

  • Yifei Zhang

Title: Open charm hadron reconstruction via hadronic decays in p+p collisions at $sqrt{s}$ = 200 GeV

Heavy quarks are believed to be an ideal probe to study the properties of the QCD medium produced in the relativistic heavy ion collisions. Heavy quark production in elementary particle collisions is expected to be better calculated in the perturbative QCD. Precision understanding on both the charm production total cross section and the fragmentation in p+p collisions is a baseline to further explore the QCD medium via open charm and charmonium in heavy ion collisions.
Early RHIC measurements in p+p collisions which were carried out via semi-leptonic decay electrons provides limited knowledge on the heavy quark production due to the incomplete kinematics, the limited momentum coverage and the mixed contribution from various charm and bottom hadrons in the electron approach. In this talk, we will present
the reconstruction of open charm hadrons (D0 and D*) via the hadronic decays in p+p collisions at $sqrt{s}$ = 200 GeV in the STAR experiment. The analysis is based on the large p+p minimum bias sample collected in RHIC Run9. The Time-Of-Flight detector, which covered 72% of the whole barrel in Run9, was used to improve the decay daughter
identification. Physics implications from this analysis will be presented.

  • Xin Li

Title: Non-photonic Electron Measurements in 200 GeV p+p collisions at RHIC-STAR

 

Compared to the light quarks, heavy quarks are produced early in the collisions and interact very differently with the strongly couple QGP(sQGP) created at RHIC. In addition, their large masses are created mostly from the spontaneous symmetry breaking. All these features make heavy quark an ideal probe to study the sQGP. One of the critical references in these studies is the heavy quark production in p+p collisions, which also provides a crucial test to the pQCD. Measuring electrons from heavy quark semi-leptonic decay (non-photonic electron) is one of the major approaches to study heavy quark production at RHIC.

We will present STAR measurements on the mid-rapidity non-photonic electron production at pT>2 GeV/c in 200 GeV p+p collisions using the datasets from the 2008 and 2005 runs, which have dramatically different photonic backgrounds. We will compare our measurements with the published results at RHIC and also report the status of the analysis at pT<2 GeV/c using the dataset from the 2009 run.

  • Jonathan Bouchet

Title: Reconstruction of charmed decays using microvertexing techniques with the STAR Silicon Detectors

Due to their production at the early stages, heavy flavor particles are of interest to study the properties of the matter created in heavy ion collisions. Direct topological reconstruction of $D$ and $B$ mesons, as opposed to indirect methods using semi-leptonic decay channels [1], provides a precise measurement and thus disentangles the $b$ and $c$ quarks contributions [2].

In this talk we present a microvertexing technique used in the reconstruction of $D^{0}$ decay vertex ($D^{0} \rightarrow K^{-}\pi^{+}$) and its charge conjugate. The significant combinatorial background can be reduced by means of
secondary vertex reconstruction and other track cut variables. Results of this method using the silicon detector information of the STAR experiment at RHIC will be presented for the Au+Au system at $\sqrt{s_{NN}}$ = 200 GeV.

[1]A. Abelev et al., Phys. Rev. Lett. {\bf 98} (2007) 192301
[2]N. Armesto et al., Phys. Lett. B{\bf 637} (2006) 362-366.

 

 

#9996# Hard Probe 2010

 Abstracts for 2010 Hard Probe Meeting (Oct. 10-15, 2010, Eilat, Israel)

 

  •  Wei Xie
Title: Heavy flavor production and heavy flavor induced correlations at RHIC

 

Heavy quarks are unique probes to study the strongly coupled Quark-Gluon Plasma created at RHIC. Unlike light quarks, heavy quark masses come mostly from spontaneous symmetry breaking, which makes them ideal for studying the medium's QCD properties. Due to their large masses, they are produced early in the collisions and are expected to interact with the medium quite differently from that of light quarks. Detailed studies on the production of open heavy flavor mesons and heavy quarkonium in heavy-ion collisions and the baseline $p+p$ and $d+A$ collisions provide crucial information in understanding the medium's properties. With the large acceptance TPC, Time of Flight, EM Calorimeter and future Heavy-Flavor Tracker, STAR has the capabilities to study heavy quark production in the dense medium in all different directions. In this talk, we will review the current status as well as the future perspectives of heavy quark studies in STAR experiment.

 

  • Zebo Tang

Title: $J/\psi$ production at high pT at STAR

 

 

 

The $c\bar{c}$ bound state $J/\psi$ provides a unique tool to probe the hot dense medium produced in heavy-ion collisions, but to date its production mechanism is not understood clearly neither in heavy-ion collisions nor in hadron hadron collisions. Measurement of $J/\psi$ production at high $p_T$ is particularly interesting since at high $p_T$
the various models give different predictions. More over some model calculations on $J/\psi$ production are only applicable at intermediate/high $p_T$. Besides, high $p_T$ particles are widely used to study the parton-medium interactions in heavy-ion collisions. In this talk, we will present the measurement of mid-rapidity (|y|<1) $J/\psi \rightarrow
e^+e^-$ production at high $p_T$ in p+p and Cu+Cu collisions at 200 GeV, that used a trigger on electron energy deposited in Electromagnetic Calorimeter. The $J/\psi$ $p_T$ spectra and nuclear modification factors will be compared to model calculations to understand its production mechanism and medium modifications. The $J/\psi$-hadron azimuthal angle correlation will be presented to disentangle $B$-mesons contributions to inclusive $J/\psi$. Progresses
from on-going analyses in p+p collisions at 200GeV taken in year 2009 high luminosity run will be also reported.

 

  • Rosi Reed

Title: $\Upsilon$ production in p+p, d+Au, Au+Au collisions at $\sqrt{{S}_{NN }} = $ 200 GeV in STAR

Quarkonia is a good probe of the dense matter produced in heavy-ion collisions at RHIC because it is produced early in the collision and the production is theorized to be suppressed due to the Debye color screening of the potential between the heavy quarks. A model dependent measurement of the temperature of the Quark Gluon Plasma (QGP) can be determined by examining the ratio of the production of various quarkonia states in heavy ion collisions versus p+p collisions because lattice calculations indicate that the quarkonia states will be sequentially suppressed. Suppression is quantified by calculating ${R}_{AA}$, which is the ratio of the production in p+p scaled by the number of binary collisions to the production in Au+Au. The $\Upsilon$ states are of particular interest because at 200 GeV the effects of feed down and co-movers are smaller than for J/$\psi$, which decreases the systematic uncertainty of the ${R}_{AA} calculation. In addition to hadronic absorption, additional cold nuclear matter effects, such as shadowing of the PDFs, can be determined from d+Au collisions. We will present our results for mid-rapidity $\Upsilon$ production in p+p, as well as our preliminary results in d+Au and Au+Au at $\sqrt{{S}_{NN }}$ = 200 GeV. These results will then be compared with theoretical QCD calculations.

  • Wei Li

Title: Non$-$Photonic Electron and Charged Hadron Azimuthal Correlation in 500 GeV p+p Collisionsions at RHIC

 

Due to the dead cone effect, heavy quarks were expected to lose less energy than light quarks since the current theory predicted that the dominant energy loss mechanism is gluon radiation for heavy quarks.  Whereas non-photonic electron from heavy quark decays show similar suppression as light hadrons at high $p_{T}$ in central Au+Au collisions.  It is important to separate the bottom contribution to non-photonic electron for the better understanding of heavy flavor
production and energy loss mechanism in ultra high energy heavy ion collisions. B decay contribution is approximately 50$\%$ at a transverse momentum of $p_{T}$$\geq$5 GeV/c in 200 GeV p+p collisions from STAR results. In this talk, we will present the azimuthal correlation analysis of non-photonic electrons with charged hadrons at $p_{T}$$\geq$6.5 GeV/c in p+p collisions at $\sqrt{s}$  = 500 GeV at RHIC. The results are compared to PYTHIA simulations to disentangle
charm and bottom contribution of semi-leptonic decays to non-photonic electrons.

 

 

  • Gang Wang

Title: B/D Contribution to Non-Photonic Electrons and Status of Non-Photonic Electron $v_2$ at RHIC

In contrast to the expectations due to the dead cone effect, non-photonic electrons from decays of heavy quark carrying hadrons show a similar suppression as light hadrons at high $p_{T}$ in central 200 GeV Au+Au collisions at RHIC. It is important to separate the charm and bottom contributions to non-photonic electrons to better understand the heavy flavor production and energy loss mechanism in high energy heavy ion collisions. Heavy quark energy loss and heavy quark evolution in the QCD medium can also lead to an elliptic flow $v_2$ of heavy quarks which can be studied through $v_2$ of non-photonic electrons.

 

In this talk, we present the azimuthal correlation analysis of non-photonic electrons with charged hadrons at 1.5 GeV/c < $p_{T}$ < 9.5 GeV/c in p+p collisions at $\sqrt{s}$ = 200 GeV at RHIC, with the removal of J/$\Psi$ contribution to non-photonic electrons. The results are compared with PYTHIA simulations to disentangle charm and bottom contributions of semi-leptonic decays to non-photonic electrons. B decay contribution is approximately 50$\%$ at the electron transverse momentum of $p_{T}$ > 5 GeV/c in 200 GeV p+p collisions from STAR results. Incorporating the spectra and energy loss information of non-photonic electrons, we further estimate the spectra and energy loss of the electrons from B/D decays. Status of $v_2$ measurements for non-photonic electrons will also be discussed for 200 GeV Au+Au collisions with RHIC run2007 data.

 

 

#9997# APS 2010 April Meeting

 Abstracts for 2010 APS April Meeting (Feb. 13-17, 2010, Washington DC)

  • Jonathan Bouchet

Title: Performance studies of the Silicon Detectors in STAR towards microvertexing of rare decays

Abstract: Heavy quarks production ($b$ and $c$) as well as their elliptic flow can be used as a probe of the thermalization of the medium created in heavy ions collisions. Direct topological reconstruction of charmed and bottom decays is then needed to obtain this precise measurement. To achieve this goal the silicon detectors of the STAR experiment are explored. These detectors, a Silicon Drift (SVT) 3-layer detector[1] and a Silicon Strip one-layer detector[2] provide tracking very near to the beam axis and allow us to search for heavy flavour with microvertexing methods. $D^{0}$ meson reconstruction including the silicon detectors in the tracking algorithm will be presented for the Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV, and physics opportunities will be discussed.

[1]R. Bellwied et al., Nucl. Inst. Methods A499 (2003) 640.

[2]L. Arnold et al., Nucl. Inst. and Methods A499 (2003) 652.

 

  • Matt Cervantes

Title: Upsilon + Hadron correlations at the Relativistic Heavy-Ion Collider (RHIC)

Abstract: STAR has the capability to reconstruct the heavy quarkonium states of both the J/Psi and Upsilon particles produced by the collisions at the Relativistic Heavy Ion Collider (RHIC).  The systematics of prompt production of heavy quarkonium is not fully described by current models, e.g. the Color Singlet Model (CSM) and the Color Octect Model.  Hadronic activity directly around the heavy quarkonium has been proposed [1] as an experimental observable to measure the radiation emitted off the coloured heavy quark pair during production.  Possible insight into the prompt production mechanism of heavy quarkonium can be obtained from this measured activity.  Using STAR data from dAu collisions at sqrt(s_NN)= 200 GeV, the high S/B ratio found in Upsilon reconstruction [2] can enable us to perform an analysis of Upsilon + Hadron correlations.  We will present our initial investigation of such an analysis.

[1] Kraan, A. C., arXiv:0807.3123.

[2] Liu, H., STAR Collaboration, arXiv:0907.4538.

PWG convener to press the approval button

 On this page, we collect the information about which PWG convener to press the final approval button for which conference.  

Conference Convener
2018 Hot Quarks Rongrong Ma
2018 Hard Probes Petr Chaloupka
2018 EJC Petr Chaloupka
2018 ATHIC Zebo Tang
2018 Zimanyi School Petr Chaloupka
2019 Bormio Rongrong Ma
2019 IIT Indore Zebo Tang
2019 QCD Moriond Petr Chaloupka
2019 APS April Meeting Sooraj Radhakrishnan
2019 QWG Zebo Tang
2019 FAIRness Zebo Tang
2019 SQM Petr Chaloupka
2019 AUM Sooraj Radhakrishnan



Presentations

This page is maintained by Gang Wang.

#9997# WWND2010

Jan 2-9, 2010 Winter Workshop on Nuclear Dynamics (Ocho Rios, Jamaica)

 

 

#9999# SQM 2009 meeting

 Sept. 27-Oct. 2, 2009 SQM 2009 meeting (Buzios, Brazil)

Proceedings

HF PWG QM2011 analysis topics

Random list of collected topics for HF PWG QM2011 (as 10.8.2010)

 

Gang Wang:  NPE v2 and possible NPE-h correlation
based on 200 GeV data

Wenqin Xu:  Non-photonic electron spectrum in available Run10 AuAu data, and calculate the R_AA

Rosi Reed: Upsilon RAA in the 200 GeV

Yifei,David,Xin: Charm hadron measurement via the hadronic decays in both Run9 p+p and
Run10 AuAu 200 GeV collisions

Zebo Tang: High-pT J/psi spectra and correlations in run9  p+p  and its R_AA in run10 200GeV Au+Au

Xin Li/ Mustafa Mustafa: Run09 p+p and Run10 Au+Au NPE cross section.

Matt Cervantes: Upsilon+hadron correlations
 

Chris Powell:  low pT J/Psi in run 10 200GeV Au+Au to obtain R_AA and polarization measurement

Barbara Trzeciak:  J/psi polarization with large
statistic p+p sample (run 9).

 

HF PWG Preliminary plots

This page collects the preliminary plots approved by the HF PWG. 
1) All the preliminary plots MUST contain a "STAR Preliminary" label.

2) Please include at least pdf and png versions for the figures

3) Where to put the data points: it is recommended to put the data point at the x position whose yield is equal to the averge yield of the bin.

 


Open Heavy Flavor

Year System Physics figures First shown Link to figures
2014+2016 Au+Au @ 200 GeV HFT: D+/- RAA 2020 HP plots
 2014+2016  Au+Au @ 200 GeV  HFT: Ds+/- spectra, ratio  2019 QM
plots 
2016 Au+Au @ 200 GeV HFT: D+/- RAA 2018 QM plots
2016 d+Au @ 200 GeV HFT: D0 2018 QM plots
2014 Au+Au @ 200 GeV HFT: D*/D0 ratio 2018 QM plots
2014+2016 Au+Au @ 200 GeV HFT: D0 v1 2018 QM plots
2014+2016 Au+Au @ 200 GeV HFT: non-prompt Jpsi 2017 QM plots
2014 Au+Au @ 200 GeV HFT: non-prompt D0  2017 QM plots
2014 Au+Au @ 200 GeV HFT: B/D->e 2017 QM plots
2014
2014+2016
Au+Au @ 200 GeV HFT: Lc/D0 Ds/Dratio
HFT:
 Lc/D0ratio
HFT: Lc/D0 Ds/D vs ALICE
2017 QM
2018 QM
2019 Moriond
plots
plots
plots

2014 Au+Au @ 200 GeV HFT: Ds RAA and v2 2017 CPOD plots
2014 Au+Au @ 200 GeV HFT: D+/- 2017 QM plots
2014 Au+Au @ 200 GeV HFT: D0 v3 2017 QM plots
2014 Au+Au @ 200 GeV D0-hadron correlation 2017 QM plots
2014 Au+Au @ 200 GeV HFT: D0 RAA
HFT: D
0 RAA
HFT: D0 RAA and v2

2019 SQM
2018 QM

2015 QM

plots
plots
plots
















         
 


Quarkonium

Year System Physics figures First shown Link to figures
 2011  p+p @ 500 GeV BEMC: Jpsi in jet  2020 HP plots
2015  p+Au @ 200 GeV  BEMC: Jpsi RpA 2020 HP plots
2016
2014
2011
Au+Au @ 200 GeV MTD/HT: Upsilon RAA 2018 QM
2017 QM
plots
plots
2015 p+p, p+Au @ 200 GeV MTD: Jpsi cross-section, RpA 2017 QM plots
2015 p+p @ 200 GeV MTD: Jpsi polarization 2017 PANIC plots
2015 p+p, p+Au @ 200 GeV BEMC: Upsilon RpAu 2017 QM plots
2014 Au+Au @ 200 GeV MTD: Jpsi RAA, v2, Upsilon ratio  2015 QM
2016 sQM
plots
2013 p+p @ 500 GeV MTD: Jpsi yield vs. event activity
2015 HP
plots
2013 p+p @ 500 GeV MTD: Jpsi cross-section 2016 sQM plots
2012 U+U @ 193 GeV MB: low-pT Jpsi excess 2016 sQM plots
2012 U+U @ 193 GeV MB/BEMC: Jpsi v2 2017 QM plots
2012 p+p @ 200 GeV MB/BEMC: Jpsi cross-section, event activity
BEMC: Jpsi polarization
2016 QWG plots
plots
2011 Au+Au @ 200 GeV MB/BEMC: Jpsi v2 2015 QM plots
2011 Au+Au @ 200 GeV MB: low-pT Jpsi excess 2016 sQM plots
2011 p+p @ 500 GeV BEMC: Jpsi cross-section WWND plots
2011 p+p @ 500 GeV HT: Upsilon cross-section
HT:
 Upsilon event activity
2017 QM
2018 PWRHIC
plots
         



Electrons from Heavy Flavor Decay

Year System Physics figures First shown Link to figures
2017  Au+Au @ 27 & 54.4 GeV  NPE v2  2020 HP  plots 
2014+2016   Au+Au @ 200 GeV HF electron: fraction, RAA, double ratio  2019 QM  plots 
2014 Au+Au @ 200 GeV NPE cross-section; RAA (without HFT) 2017 QM plots
2012 p+p @ 200 GeV NPE-hadron correlation, b fraction 2016 Santa Fe plots
2012 p+p @ 200 GeV NPE cross-section; udpated RAA 2015 QM plots
         










 

Heavy Quark Physics in Nucleus-Nucleus Collisions Workshop at UCLA

We will organize a workshop on heavy quark physics in nucleus-nucleus collisions from January 22-24, 2009. The workshop will be hosted by the Department of Physics and Astronomy, University of California at Los Angeles.

Topics of the workshop include
1) Contrasting heavy quark and light quark energy loss mechanisms,
2) Charm and Bottom quark energy loss phenomenology,
3) Quantifying QCD matter using heavy quark probes,
4) Color screening and Quarkonia propagation/generation,
and 5) Update on plan of heavy quark measurements/detector upgrades at LHC/RHIC.
 
The workshop web site is
http://home.physics.ucla.edu/calendar/Workshops/HQP/index.html.

 

NPE Analyses

 

PicoDst production requests

 This page collects the picoDst (re)production requested made by the HF PWG

Priority Dataset Data stream Special needs Chain option Production status  Comments
0 production_pAu200_2015 st_physics
st_ssdmb
BEMC PicoVtxMode:PicoVtxVpdOrDefault, TpcVpdVzDiffCut:6  Done with SL18b Needed for QM2018
2 dAu200_production_2016 st_physics BEMC, FMS PicoVtxMode:PicoVtxVpdOrDefault, TpcVpdVzDiffCut:6
Benefit QM2018 analysis
3 production_pAu200_2015 st_mtd BEMC PicoVtxMode:PicoVtxVpdOrDefault, TpcVpdVzDiffCut:6

4 AuAu200_production_2016
AuAu200_production2_2016
st_physics BEMC, FMS PicoVtxMode:PicoVtxVpdOrDefault, TpcVpdVzDiffCut:3    
5 AuAu_200_production_2014
AuAu_200_production_low_2014
AuAu_200_production_mid_2014
AuAu_200_production_high_2014
st_mtd

BEMC mtdMatch, y2014a, PicoVtxMode:PicoVtxVpdOrDefault, TpcVpdVzDiffCut:3    
1 AuAu_200_production_low_2014
AuAu_200_production_mid_2014
st_physics BEMC mtdMatch, y2014a, PicoVtxMode:PicoVtxVpdOrDefault, TpcVpdVzDiffCut:3    
6 production_pp200long_2015
production_pp200long2_2015
production_pp200long3_2015
production_pp200trans_2015
st_physics
st_ssdmb
BEMC mtdMatch, y2015c,PicoVtxMode:PicoVtxVpdOrDefault, TpcVpdVzDiffCut:6    
  production_pp200_2015 st_mtd   mtdMatch, y2015c, PicoVtxMode:PicoVtxVpdOrDefault, TpcVpdVzDiffCut:6, PicoCovMtxMode:PicoCovMtxSkip    


Upsilon Analysis

Links related to Upsilon Analysis.

  • Upsilon paper page from Pibero.
  • Technical Note is located in Attachments to this page.
  • TeX source (saved as .txt so drupal doesn't complain) for Technical Note is also in Attachments.
  • Upsilon paper drafts are found below.

 

Combinatorial background subtraction for e+e- signals

It is common to use the formula 2*sqrt(N++ N--) to model the combinatorial background when studying e+e- signals, e.g. for J/psi and Upsilon analyses.  We can obtain this formula in the following way.

Assume we have an event in which there are Nsig particles that decay into e+e- pairs.  Since each decay generates one + and one - particle, the total number of unlike sign combinations we can make is N+- = Nsig2. To obtain the total number of pairs that are just random combinations, we subtract the number of pairs that came from a real decay.  So we have

N+-comb=Nsig2-Nsig=Nsig(Nsig-1)

For the number of like-sign combinations, for example for the ++ combinations, there will be a total of (Nsig-1) pairs that can be made by the first positron, then (Nsig-2) that can be made by the second positron, and so on.  So the total number of ++ combinations will be

N++ = (Nsig-1) + (Nsig - 2) + ... + (Nsig - (Nsig-1)) + (Nsig-Nsig)

Where there are Nsig terms. Factoring, we get:

N++ = Nsig2 - (1+2+...+Nsig) = Nsig2 - (Nsig(Nsig+1))/2 = (Nsig2 - Nsig)/2=Nsig(Nsig-1)/2

Similarly,

N-- = Nsig(Nsig-1)/2

If there are no acceptance effects, either the N++ or the N-- combinations can be used to model the combinatorial background by simply multiplying them by 2.  The geometric average also works:

2*sqrt(N++ N--) = 2*Nsig(Nsig-1)/sqrt(4) = Nsig(Nsig-1) = N+-comb.

The geometric average can also work for cases where there are acceptance differences, with the addition of a multiplicative correction factor R to take the relative acceptance of ++ and -- pairs into account. So the geometric average is for the case R=1 (similar acceptance for ++ and --).

Estimating Acceptance Uncertainty due to unknown Upsilon Polarization

The acceptance of Upsilon decays depends on the polarization of the Upsilon.  We do not have enough statistics to measure the polarization.  It is also not clear even at higher energies if there is a definite pattern: there are discrepancies between CDF and D0 about the polarization of the 1S.  The 2S and 3S show different polarizations trends than the 1S. So for the purposes of the paper, we will estimate the uncertainty due to the unknown Upsilon polarization using two extremes: fully transverse and fully longitudinal polarization.  This is likely an overestimate, but the effect is not the dominant source of uncertainty, so for the paper it is good enough.

There are simulations of the expected acceptance for the unpolarized, longitudinal and transverse cases done by Thomas:

http://www.star.bnl.gov/protected/heavy/ullrich/ups-pol.pdf

Using the pT dependence of the acceptance for the three cases (see page 9 of the PDF) we must then apply it to our measured upsilons.  We do this by obtaining the pT distribution of the unlike sign pairs (after subtracting the like-sign combinatorial background) in the Upsilon mass region and with |y|<0.5.  This is shown below as the black data points.

The data points are fit with a function of the form A pT2  exp(-pT/T), shown as the solid black line (fit result: A=18.0 +/- 8.3, T = 1.36 +/- 0.16 GeV/c).  We then apply the correction for the three cases, shown in the histograms (with narrow line width).  The black is the correction for the unpolarized case (default), the red is for the longitudinal and the blue is for the transverse case.  The raw yield can be obtained by integrating the histogram or the function.  These give 89.7 (histo) and 89.9 (fit), which given the size of the errors is a reasonable fit.  We can obtain the acceptance corrected  yield (we ignore all other corrections here) by integrating the histograms, which give:

  • Unpol: 158.9 counts
  • Trans: 156.4 counts
  • Longi: 163.6 counts

We estimate from this that fully transverse Upsilons should have a yield lower by -1.6% and fully longitudinal Upsilons should have a higher yield by 2.9%.  We use this as a systematic uncertainty in the acceptance correction. 

In addition, the geometrical acceptance can vary in the real data due to masked towers which are not accounted for in the simulation.  We estimate that this variation is of order 25 towers (which is used in the 2007 and 2008 runs as the number of towers allowed to be dynamically masked). This adds 25/4800 = 0.5% to the uncertainty in the geometrical acceptance.

Estimating Drell-Yan contribution from NLO calculation.

Ramona calculated the cross section for DY at NLO and sent the data points to us.  These were first shown in the RHIC II Science Workshop, April 2005, in her Quarkonium talk and her Drell-Yan (and Open heavy flavor) talk.

The total cross section (integral of all mass points in the region |y|<5) is 19.6 nb (Need to check if there is an additional normalization with Ramona, but the cross section found by PHENIX using Pythia is 42 nb with 100% error bar, so a 19.6 nb cross section is certainly consistent with this). She also gave us the data in the region |y|<1, where the cross section is 5.24 nb. The cross section as a function of invariant mass in the region |y|<1 is shown below.

The black curve includes a multiplication with an error function (as we did for the b-bbar case) and normalized such that the ratio between the blue and the black line is 8.5% at 10 GeV/c to account for the efficiency and acceptance found in embedding for the Upsilon 1s.  The expected counts in the region 8-11 are 20 +/- 3, where the error is given by varying the parameters of the error function within its uncertainty.  The actual uncertainty is likely bigger than this if we take into account the overall normalization uncertainty in the calculation.

I asked Ramona for the numbers in the region |y|<0.5, since that is what we use in STAR.  The corresponding plot is below.

 The integral of the data points gives 2.5 nb.  The integral of the data between 7.875 and 11.125 GeV/c2 is 42.30 pb.  The data is parameterized by the function shown in blue.  The integral of the function in the same region gives 42.25 pb, so it is quite close to the calculation.  In the region 8<m<11 GeV/c2, the integral of the funciton is 38.6 pb.  The expected counts with this calculation are 25 for both triggers.

Response to PRD referee comments on Upsilon Paper

First Round of Referee Responses

Click here for second round.

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> Report of Referee A:
> -------------------------------------------------------------------------
>
> This is really a well-written paper. It was a pleasure to read, and I
> have only relatively minor comments.

We thank the reviewer for careful reading of our paper and for providing
useful feedback. We are pleased to know that the reviewer finds the
paper to be well written. We have incorporated all the comments into a
new version of the draft.

> Page 3: Although there aren't published pp upsilon cross sections there
> is a published R_AA and an ee mass spectrum shown in E. Atomssa's QM09
> proceedings. This should be referenced.

We are aware of the PHENIX results from
E. Atomssa, Nucl.Phys.A830:331C-334C,2009
and three other relevant QM proceedings:
P. Djawotho, J.Phys.G34:S947-950,2007
D. Das, J.Phys.G35:104153,2008
H. Liu, Nucl.Phys.A830:235C-238C,2009
However, it is STAR's policy to not reference our own preliminary data on the manuscript we submit for publication on a given topic, and by extension not to reference other preliminary experimental data on the same topic either.

>
> Page 4, end of section A: Quote trigger efficiency.
>

The end of Section A now reads:
"We find that 25% of the Upsilons produced at
midrapidity have both daughters in the BEMC acceptance and at least one
of them can fire the L0 trigger. The details of the HTTP
trigger efficiency and acceptance are discussed in Sec. IV"

> Figure 1: You should either quote L0 threshold in terms of pt, or plot
> vs. Et. Caption should say L0 HT Trigger II threshold.

We changed the figure to plot vs. E_T, which is the quantity that is
measured by the calorimeter. For the electrons in the analysis, the
difference between p_T and E_T is negligible, so the histograms in
Figure 1 are essentially unchanged. We changed the caption as suggested.

>
> Figures 3-6 would benefit from inclusion of a scaled minimum bias spectrum
> to demonstrate the rejection factor of the trigger.

We agree that it is useful to quote the rejection factor of the trigger.
We prefer to do so in the text. We added to the description of Figure
3 the following sentence: "The rejection factor achieved with Trigger
II, defined as the number of minimum bias events counted by the trigger scalers
divided by the number events where the upsilon trigger was issued, was
found to be 1.8 x 105."

>
> Figure 9: There should be some explanation of the peak at E/p = 2.7
>

We investigated this peak, and we traced it to a double counting error.
The problem arose due to the fact that the figure was generated from
a pairwise Ntuple, i.e. one in which each row represented a pair of
electrons (both like-sign and unlike-sign pairs included), each with a
value of E and p, instead of a single electron Ntuple. We had plotted
the value of E/p for the electron candidate which matched all possible
high-towers in the event. The majority of events have only one candidate
pair, so there were relatively few cases where there was double
counting. We note that for pairwise quantities such as opening angle and
invariant mass, each entry in the Ntuple is still different. However,
the case that generated the peak at E/p = 2.7 in the figure was traced
to one event that had one candidate positron track, with its
corresponding high-tower, which was paired with several other electron
and positron candidates. Each of these entries has a different invariant
mass, but the same E/p for the first element of the pair. So its entry
in Figure 9, which happened to be at E/p=2.7, was repeated several times
in the histogram. The code to generate the data histogram in Figure 9
has now been corrected to guarantee that the E/p distribution is made
out of unique track-cluster positron candidates. The figure in the paper
has been updated. The new histogram shows about 5 counts in that
region. As a way to gauge the effect the double counting had on the
E/p=1 area of the figure, there were about 130 counts in the figure at
the E/p=1 peak position in the case with the double-counting error, and
there are about 120 counts in the peak after removing the
double-counting. The fix leads to an improved match between the data
histogram and the Monte Carlo simulations. We therefore leave the
efficiency calculation, which is based on the Monte Carlo Upsilon
events, unchanged. The pairwise invariant mass distribution from which
the main results of the paper are obtained is unaffected by this. We
thank the reviewer for calling our attention to this peak, which allowed
us to find and correct this error.

>
> -------------------------------------------------------------------------
> Report of Referee B:
> -------------------------------------------------------------------------
>
> The paper reports the first measurement of the upsilon (Y) cross-section
> in pp collisions at 200 GeV. This is a key piece of information, both
> in the context of the RHIC nucleus-nucleus research program and in its
> own right. The paper is rather well organized, the figures are well
> prepared and explained, and the introduction and conclusion are clearly
> written. However, in my opinion the paper is not publishable in its
> present form: some issues, which I enumerate below, should be addressed
> by the authors before that.
>
> The main problems I found with the paper have to do with the estimate
> of the errors. There are two issues:
>
> The first: the main result is obtained by integrating the counts above
> the like-sign background between 8 and 11 GeV in figure 10, quoted to
> give 75+-20 (bottom part of table III). This corresponds the sum Y +
> continuum. Now to get the Y yield, one needs to subtract an estimated
> contribution from the continuum. Independent of how this has been
> estimated, the subtraction can only introduce an additional absolute
> error. Starting from the systematic error on the counts above background,
> the error on the estimated Y yield should therefore increase, whereas
> in the table it goes down from 20 to 18.

Thanks for bringing this issue to our attention. It is true that when
subtracting two independently measured numbers, the statistical
uncertainty in the result of the subtraction can only be larger than the
absolute errors of the two numbers, i.e. if C = A - B, and error(A) and
error(B) are the corresponding errors, then the statistical error on C
would be sqrt(error(B)2+error(A)2) which would yield a larger absolute
error than either error(A) or error(B). However, the extraction of the
Upsilon yield in the analysis needs an estimate of the continuum
contribution, but the key difference is that it is not obtained by an
independent measurement. The two quantities, namely the Upsilon yield
and the continuum yield, are obtained ultimately from the same source:
the unlike sign dielectron distribution, after the subtraction of the
like-sign combinatorial background. This fact causes an
anti-correlation between the two yields, the larger the continuum yield,
the smaller the Upsilon yield. So one cannot treat the subtraction of
the continuum yield and the Upsilon yield as the case for independent
measurements. This is why in the paper we discuss that an advantage of
using the fit includes taking automatically into account the correlation
between the continuum and the Upsilon yield. So the error that is
quoted in Table III for all the "Upsilon counts", i.e. the Fitting
Results, the Bin-by-bin Counting, and the Single bin counting, is quoted
by applying the percent error on the Upsilon yield obtained from the
fitting method, which is the best way to take the anti-correlation
between the continuum yield and the Upsilon yield into account. We will
expand on this in section VI.C, to help clarify this point. We thank the referee for
alerting us.

>
> The second issue is somewhat related: the error on the counts (18/54, or
> 33%) is propagated to the cross section (38/114) as statistical error,
> and a systematic error obtained as quadratic sum of the systematic
> uncertainties listed in Table IV is quoted separately. The uncertainty on
> the subtraction of the continuum contribution (not present in Table IV),
> has completely disappeared, in spite of being identified in the text as
> "the major contribution to the systematic uncertainty" (page 14, 4 lines
> from the bottom).
>
> This is particularly puzzling, since the contribution of the continuum
> is even evaluated in the paper itself (and with an error). This whole
> part needs to be either fixed or, in case I have misunderstood what the
> authors did, substantially clarified.

We agree that this can be clarified. The error on the counts (18/54, or
33%) includes two contributions:
1) The (purely statistical) error on the unlike-sign minus like sign
subtraction, which is 20/75 or 26%, as per Table III.
2) The additional error from the continuum contribution, which we
discuss in the previous comment, and is not just a statistical sum of
the 26% statistical error and the error on the continuum, rather it must
include the anti-correlation of the continuum yield and the Upsilon
yield. The fit procedure takes this into account, and we arrive at the
combined 33% error.

The question then arises how to quote the statistical and systematic
uncertainties. One difficulty we faced is that the subtraction of the
continuum contribution is not cleanly separated between statistical and
systematic uncertainties. On the one hand, the continuum yield of 22
counts can be varied within the 1-sigma contours to be as low as 14 and
as large as 60 counts (taking the range of the DY variation from Fig.
12). This uncertainty is dominated by the statistical errors of the
dielectron invariant mass distribution from Fig. 11. Therefore, the
dominant uncertainty in the continuum subtraction procedure is
statistical, not systematic. To put it another way, if we had much
larger statistics, the uncertainty in the fit would be much reduced
also. On the other hand, there is certainly a model-dependent component
in the subtraction of the continuum, which is traditionally a systematic
uncertainty. We chose to represent the combined 33% percent error as a
statistical uncertainty because a systematic variation in the results
would have if we were to choose, say, a different model for the continuum
contribution, is smaller compared to the variation allowed by the
statistical errors in the invariant mass distribution. In other words,
the reason we included the continuum subtraction uncertainty together in
the quote of the statistical error was that its size in the current
analysis ultimately comes from the statistical precision of our
invariant mass spectrum. We agree that this is not clear in the text,
given that we list this uncertainty among all the other systematic
uncertainties, and we have modified the text to clarify this. Perhaps a
more appropriate way to characterize the 33% error is that it includes
the "statistical and fitting error", to highlight the fact that in
addition to the purely statistical errors that can be calculated from
the N++, N-- and N+- counting statistics, this error includes the
continuum subtraction error, which is based on a fit that takes into
account the statistical error on the invariant mass spectrum, and the
important anti-correlation between the continuum yield and the Upsilon
yield. We have added an explanation of these items in the updated draft of
the paper, in Sec VI.C.

>
> There are a few other issues which in my opinion should be dealt with
> before the paper is fit for publication:
>
> - in the abstract, it is stated that the Color Singlet Model (CSM)
> calculations underestimate the Y cross-section. Given that the discrepancy
> is only 2 sigma or so, such a statement is not warranted. "Seems to
> disfavour", could perhaps be used, if the authors really insist in making
> such a point (which, however, would be rather lame). The statement that
> CSM calculations underestimate the cross-section is also made in the
> conclusion. There, it is even commented, immediately after, that the
> discrepancy is only a 2 sigma effect, resulting in two contradicting
> statements back-to-back.

Our aim was mainly to be descriptive. To clarify our intent, the use of
"underestimate" is in the sense that if we move our datum point lower by the
1-sigma error of our measurement and this value is higher than the top
end of the CSM calculation. We quantify this by saying that the
size of the effect is about 2-sigma. We think that the concise statement
"understimate by 2sigma" objectively summarizes the observation, without
need to use more subjective statements, and we modified
the text in the abstract and conclusion accordingly.

>
> - on page 6 it is stated that the Trigger II cuts were calculated offline
> for Trigger I data. However, it is not clear if exactly the same trigger
> condition was applied offline on the recorded values of the original
> trigger input data or the selection was recalculated based on offline
> information. This point should be clarified.

Agreed. We have added the sentence: "The exact same trigger condition was
applied offline on the recorded values of the original trigger input data."

>
> - on page 7 it is said that PYTHIA + Y events were embedded in zero-bias
> events with a realistic distribution of vertex position. Given that
> zero-bias events are triggered on the bunch crossing, and do not
> necessarily contain a collision (and even less a reconstructed vertex),
> it is not clear what the authors mean.

We do not know if the statement that was unclear is how the realsitic
vertex distribution was obtained or if the issue pertained to where the analyzed collision comes from.
We will try to clarify both instances. The referee has correctly understood
that the zero-bias events do not necessarily contain a collision.
That is why the PYTHIA simulated event is needed. The zero-bias events
will contain additional effects such as out of time pile-up in the Time
Projection Chamber, etc. In other words, they will contain aspects of
the data-taking environment which are not captured by the PYTHIA events.
That is what is mentioned in the text:

"These zero-bias events do not always have a collision in the given
bunch crossing, but they include all the detec-
tor effects and pileup from out-of-time collisions. When
combined with simulated events, they provide the most
realistic environment to study the detector e±ciency and
acceptance."

The simulated events referred to in this text are the PYTHIA events, and
it is the simulated PYTHIA event, together with the Upsilon, that
provides the collision event to be studied for purposes of acceptance
and efficiency. In order to help clarify our meaning, we have also added
statements to point out that the dominant contribution to the TPC occupancy
is from out of time pileup.
Regarding the realistic distribution of vertices,
this is obtained from the upsilon triggered events (not from the zero-bias events, which
have no collision and typically do not have a found vertex, as the referee correctly
interpreted). We have added a statement to point this out and hopefully this will make
the meaning clear.

>
> - on page 13 the authors state that they have parametrized the
> contribution of the bbar contribution to the continuum based on a PYTHIA
> simulation. PYTHIA performs a leading order + parton shower calculation,
> while the di-electon invariant mass distribution, is sensitive to
> next-to-leading order effects via the angular correlation of the the two
> produced b quarks. Has the maginuted of this been evaluated by comparing
> PYTHIA results with those of a NLO calculation?
>

We did not do so for this paper. This is one source of systematic
uncertainty in the continuum contribution, as discussed in the previous
remarks. For this paper, the statistics in the dielectron invariant
mass distribution are such that the variation in the shape of the b-bbar
continuum between LO and NLO would not contribute a significant
variation to the Upsilon yield. This can be seen in Fig. 12, where the
fit of the continuum allows for a removal of the b-bbar yield entirely,
as long as the Drell-Yan contribution is kept. We expect to make such
comparisons with the increased statistics available in the run 2009
data, and look forward to including NLO results in the next analysis.

> - on page 13 the trigger response is emulated using a turn-on function
> parametrised from the like-sign data. Has this been cross-checked with a
> simulation? If yes, what was the result? If not, why?

We did not cross check the trigger response on the continuum with a
simulation, because a variation of the turn-on function parameters gave
a negligible variation on the extracted yields, so it was not deemed
necessary. We did use a simulation of the trigger response on simulated
Upsilons (see Fig. 6, dashed histogram).

>
> Finally, I would like to draw the attention of the authors on a few less
> important points:
>
> - on page 6 the authors repeat twice, practically with the same words,
> that the trigger rate is dominated by di-jet events with two back-to-back
> pi0 (once at the top and once near the bottom of the right-side column).

We have changed the second occurrence to avoid repetitiveness.

>
> - all the information of Table I is also contained in Table 4; why is
> Table I needed?

We agree that all the information in Table I is contained in Table 4
(except for the last row, which shows the combined efficiency for the
1S+2S+3S), so it could be removed. We have included it for convenience
only: Table I helps in the discussion of the acceptance and
efficiencies, and gives the combined overall correction factors, whereas
the Table IV helps in the discussion of the systematic uncertainties of
each item.

>
> - in table IV, the second column says "%", which is true for the
> individual values of various contributions to the systematic uncertainty,
> but not for the combined value at the bottom, which instead is given
> in picobarn.

Agreed. We have added the pb units for the Combined error at the bottom of the
table.

>
> - in the introduction (firts column, 6 lines from the bottom) the authors
> write that the observation of suppression of Y would "strongly imply"
> deconfinement. This is a funny expression: admitting that such an
> observation would imply deconfinement (which some people may not be
> prepared to do), what's the use of the adverb "strongly"? Something
> either does or does not imply something else, without degrees.

We agree that the use of "imply" does not need degrees, and we also
agree that some people might not be prepared to admit that such an
observation would imply deconfinement. We do think that such an
observation would carry substantial weight, so we have rephrased that
part to "An observation of suppression of Upsilon
production in heavy-ions relative to p+p would be a strong argument
in support of Debye screening and therefore of
deconfinement"

We thank the referee for the care in reading the manuscript and for all
the suggestions.

Second Round of Referee Responses

> I think the paper is now much improved. However,
> there is still one point (# 2) on which I would like to hear an
> explanation from the authors before approving the paper, and a
> couple of points (# 6 and 7) that I suggest the authors should
> still address.
> Main issues:
> 1) (errors on subtraction of continuum contribution)
> I think the way this is now treated in the paper is adequate
> 2) (where did the subtraction error go?)
> I also agree that the best way to estimate the error is
> to perform the fit, as is now explicitly discussed in the paper.
> Still, I am surprised, that the additional error introduced by
> the subtraction of the continuum appears to be negligible
> (the error is still 20). In the first version of the paper there
> was a sentence – now removed – stating that the uncertainty
> on the subtraction of the continuum contribution was one
> of the main sources of systematic uncertainty!
> -> I would at least like to hear an explanation about
> what that sentence
> meant (four lines from the bottom of page 14)

Response:
Regarding the size of the error:
The referee is correct in observing that the error before
and after subtraction is 20, but it is important to note
that the percentage error is different. Using the numbers
from the single bin counting, we get
75.3 +/- 19.7 for the N+- - 2*sqrt(N++ * N--),
i.e. the like-sign subtracted unlike-sign signal. The purely
statistical uncertainty is 19.7/75.3 = 26%. When we perform
the fit, we obtain the component of this signal that is due
to Upsilons and the component that is due to the Drell-Yan and
b-bbar continuum, but as we discussed in our previous response,
the yields have an anti-correlation, and therefore there is no
reason why the error in the Upsilon yield should be larger in
magnitude than the error of the like-sign subtracted unlike-sign
signal. However, one must note that the _percent_ error does,
in fact, increase. The fit result for the upsilon yield alone
is 59.2 +\- 19.8, so the error is indeed the same as for the
like-sign subtracted unlike-sign signal, but the percent error
is now larger: 33%. In other words, the continuum subtraction
increases the percent error in the measurement, as it should.
Note that if we one had done the (incorrect) procedure of adding
errors in quadrature, using an error of 14.3 counts for the
continuum yield and an error of 19.7 counts for the
background-subtracted unlike-sign signal, the error on the
Upsilon yield would be 24 counts. This is a relative error of 40%, which
is larger than the 33% we quote. This illustrates the effect
of the anti-correlation.

Regarding the removal of the sentence about the continuum
subtraction contribution to the systematic uncertainty:
During this discussion of the continuum subtraction and
the estimation of the errors, we decided to remove the
sentence because, as we now state in the paper, the continuum
subtraction uncertainty done via the fit is currently
dominated by the statistical error bars of the data in Fig. 11,
and is therefore not a systematic uncertainty. A systematic
uncertainty in the continuum subtraction would be estimated,
for example, by studying the effect on the Upsilon yield that
a change from the Leading-Order PYTHIA b-bbar spectrum we use
to a NLO b-bbar spectrum, or to a different Drell-Yan parameterization.
As discussed in the response to point 6), a complete
removal of the b-bbar spectrum, a situation allowed by the fit provided
the Drell-Yan yield is increased, produces a negligible
change in the Upsilon yield. Hence, systematic variations
in the continuum do not currently produce observable changes
in the Upsilon yield. Varying the continuum yield
of a given model within the statistical error bars does, and
this uncertainty is therefore statisitcal. Therefore, we removed the
sentence stating that the continuum subtraction is one
of the dominant sources of systematic uncertainty because
in the reexamination of that uncertainty triggered by the
referee's comments, we concluded that it is more appropriate
to consider it as statistical, not systematic, in nature.
We have thus replaced that sentence, and in its stead
describe the uncertainty in the cross
section as "stat. + fit", to draw attention to the fact that
this uncertainty includes the continuum subtraction uncertainty
obtained from the fit to the data. The statements in the paper
in this respect read (page 14, left column):

It should be noted that
with the statistics of the present analysis, we find that the
allowed range of variation of the continuum yield in the fit is
still dominated by the statistical error bars of the invariant mass
distribution, and so the size of the 33% uncertainty is mainly
statistical in nature. However, we prefer to denote
the uncertainty as “stat. + fit” to clarify that it includes the estimate of the anticorrelation
between the Upsilon and continuum yields obtained
by the fitting method. A systematic uncertainty due to
the continuum subtraction can be estimated by varying
the model used to produce the continuum contribution
from b-¯b. These variations produce a negligible change in
the extracted yield with the current statistics.

We have added our response to point 6) (b-bbar correlation systematics)
to this part of the paper, as it pertains to this point.

> Other issues:
> 3) (two sigma effect)
> OK
> 4) (Trigger II cuts)
> OK
> 5) (embedding)
> OK
> 6) (b-bbar correlation)
> I suggest adding in the paper a comment along the lines of what
> you say in your reply
> 7) (trigger response simulation)
> I suggest saying so explicitly in the paper

Both responses have been added to the text of the paper.
See page 13, end of col. 1, (point 7) and page 14, second column (point 6).

> Less important points:
> 8) (repetition)
> OK
> 9) (Table I vs Table IV)
> OK…
> 10) (% in last line of Table IV)
> OK
> 11) (“strongly imply”)
> OK

We thank the referee for the care in reading the manuscript, and look forward to
converging on these last items.

 

Upsilon Analysis in d+Au 2008

Upsilon yield and nuclear modification factor in d+Au collisions at sqrt(s)=200 GeV.

PAs: Anthony Kesich, and Manuel Calderon de la Barca Sanchez.

 

  • Dataset QA
    • Trigger ID, runs
      • Trigger ID = 210601
        • ZDC East signal + BEMC HT at 18 (Et>4.3 GeV) + L2 Upsilon
        • Total Sampled Luminosity: 32.66 nb^-1; 1.216 Mevents
          • http://www.star.bnl.gov/protected/common/common2008/trigger2008/lum_pertriggerid_dau2008.txt
      •  
    • Run by Run QA
    • Integrated Luminosity estimate
    • Systematic Uncertainty
  • Acceptance (Check with Kurt Hill)
    • Raw pT, y distribution of Upsilon
    • Accepted pT, y distribution of Upsilons
    • Acceptance
    • Raw pT, eta distribution of e+,e- daughters
    • Accepted pT, eta distribution of e+,e- daughters
    • Comparison plots between single-electron embedding, Upsilon embedding
  • L0 Trigger
    • DSM-ADC Distribution (data, i.e. mainly background)
    • DSM-ADC Distribution (Embedding) For accepted Upsilons, before and after L0 trigger selection
    • Systematic Uncertainty (Estimate of possible calibration and resolution systematic offsets).
    • "highest electron/positron Et" distribution from embedding (Accepted Upsilons, before and after L0 trigger selection)
  • L2 Trigger
    • E1 Cluster Et distribution (data, i.e. mainly background)
    • E1 Cluster Et distribution (embedding, L0 triggered, before and after all L2 trigger cuts)
    • L2 pair opening angle (cos theta) data (i.e.  mainly background)
    • L2 pair opening angle (cos theta) embedding. Needs map of (phi,eta)_MC to (phi,eta)_L2 from single electron embedding. Then a map from r1=(phi,eta, R_emc) to r1=(x,y,z) so that one can do cos(theta^L2) = r1.dot(r2)/(r1.mag()*r2.mag()). Plot cos theta distribution for L0 triggered events, before and after all L2 trigger cuts. (Kurt)
    • L2 pair invariant mass from data (i.e. mainly background)
    • L2 pair invariant mass from embedding. Needs simulation as for cos(theta), so that one can do m^2 = 2 * E1 * E2 * (1 - cos(theta)) where E1 and E2 are the L2 cluster energies. Plot the invariant mass distribution fro L0 triggered events, before and after all L2 trigger cuts. (Check with Kurt)
  • PID
    • dE/dx
      • dE/dx vs p for the Upsilon triggered data
      • nsigma_dE/dx calibration of means and sigmas (done by C. Powell for his J/Psi work)
      • Cut optimization (Maximization of electron effective signal)
      • Final cuts for use in data analysis
    • E/p
      • E/p distributions for various p bins
      • Study of E calibration and resolution between data and embedding (for L0 Trigger systematic uncertainty)
      • Resolution and comparison with embedding (for cut efficiency estimation)
  • Yield extraction
  • Cross section calculation.
    • Yield, dN/dy
    • Integrated luminosity (for 1/N_events, where N_events were the total events sampled by the L0 trigger)
    • Efficiency (Numbers for each state, and cross-section-branching-ratio-weighted average)
    • Uncertainty
    • pt Distribution (invariant, i.e. 1/N_event 1/2pi, 1/pt dN/dpt dy) in |y|<0.5 vs pt) This might need one to do the CB, DY, bbbar fit in pt bins.
  • Nuclear Modification Factor
    • Estimation of <Npart> for the dataset, and uncertainty.
    • Putting it all together: dN/dy in dAu, Npart, Luminosity (N_events), divided by the pp numbers (dsigma/dy, sigma_pp)
    • Plot of R_dAu vs y, comparison with theory
    • Plot of R_dAu vs Npart, together with Au+Au
    • Plot of R_dAu vs pt.  Try to do together with Au+Au (minbias, maybe in centrality bins, but maybe not enough stats)

 

Upsilon Analysis in p+p 2009

Upsilon cross-section in p+p collisions at sqrt(sNN) = 200 GeV, 2009 data.

PAs: Kurt Hill, Andrew Peterson, Gregory Wimsatt, Anthony Kesich, Rosi Reed, Manuel Calderon de la Barca Sanchez.

  • Dataset QA (Andrew Peterson)
    • Trigger ID, runs
    • Run by Run QA
    • Integrated Luminosity estimate
    • Systematic Uncertainty
  • Acceptance (Kurt Hill)
    • Raw pT, y distribution of Upsilon
    • Accepted pT, y distribution of Upsilons
    • Acceptance
    • Raw pT, eta distribution of e+,e- daughters
    • Accepted pT, eta distribution of e+,e- daughters
    • Comparison plots between single-electron embedding, Upsilon embedding
  • L0 Trigger
    • DSM-ADC Distribution (data, i.e. mainly background) (Drew)
    • DSM-ADC Distribution (Embedding) For accepted Upsilons, before and after L0 trigger selection
    • Systematic Uncertainty (Estimate of possible calibration and resolution systematic offsets).
    • "highest electron/positron Et" distribution from embedding (Accepted Upsilons, before and after L0 trigger selection)
  • L2 Trigger
    • E1 Cluster Et distribution (data, i.e. mainly background)
    • E1 Cluster Et distribution (embedding, L0 triggered, before and after all L2 trigger cuts)
    • L2 pair opening angle (cos theta) data (i.e.  mainly background)
    • L2 pair opening angle (cos theta) embedding. Needs map of (phi,eta)_MC to (phi,eta)_L2 from single electron embedding. Then a map from r1=(phi,eta, R_emc) to r1=(x,y,z) so that one can do cos(theta^L2) = r1.dot(r2)/(r1.mag()*r2.mag()). Plot cos theta distribution for L0 triggered events, before and after all L2 trigger cuts. (Kurt)
    • L2 pair invariant mass from data (i.e. mainly background)
    • L2 pair invariant mass from embedding. Needs simulation as for cos(theta), so that one can do m^2 = 2 * E1 * E2 * (1 - cos(theta)) where E1 and E2 are the L2 cluster energies. Plot the invariant mass distribution fro L0 triggered events, before and after all L2 trigger cuts. (Kurt)
  • PID (Greg)
    • dE/dx
      • dE/dx vs p for the Upsilon triggered data
      • nsigma_dE/dx calibration of means and sigmas
      • Cut optimization (Maximization of electron effective signal)
      • Final cuts for use in data analysis
    • E/p
      • E/p distributions for various p bins
      • Study of E calibration and resolution between data and embedding (for L0 Trigger systematic uncertainty)
      • Resolution and comparison with embedding (for cut efficiency estimation) (Kurt and Greg)
  • Yield extraction
    • Invariant mass distributions
      • Unlike-sign and Like-sign inv. mass (Drew)
      • Like-sign subtracted inv. mass (Drew)
      • Crystal-Ball shapes from embedding/simulation. (Kurt) Crystal-ball parameters to be used in fit (Drew)
    • Fit to Like-sign subtracted inv. mass, using CB, DY, b-bbar.
      • Contour plot (1sigma and 2sigma) of b-bbar cross section vs. DY cross section. (Drew)
      • Upsilon yield estimation and stat. + fit error. (Drew)
    • (2S+3S)/1S (Drew)
  • pT Spectra (Drew)
  • Cross section calculation.
    • Yield
    • Integrated luminosity
    • Efficiency (Numbers for each state, and cross-section-branching-ratio-weighted average)
    • Uncertainty
  • h+/h- Corrections

Upsilon Analysis in p+p 2009 - L0 Trigger

 

2009 BTOW Calibrations

Upsilon Analysis in p+p 2009 data - Acceptance

  • Acceptance (Kurt Hill)  -  Upsilon acceptance aproximated using a simulation that constructs Upsilons (flat in pT and y), lets them decay to e+e- pairs in the Upsilon's rest frame, and uses detector response functions generated from a single electron embedding to model detector effects.  An in depth study of this method will also be included.
    • Raw pT, y distribution of Upsilon
    • Accepted pT, y distribution of Upsilons
    • Acceptance
    • Raw pT, eta distribution of e+,e- daughters
    • Accepted pT, eta distribution of e+,e- daughters
    • Comparison plots between single-electron embedding, Upsilon embedding

Upsilon Analysis in p+p 2009 data - Acceptance

  • Acceptance (Kurt Hill)
    • Raw pT, y distribution of Upsilon
    • Accepted pT, y distribution of Upsilons
    • Acceptance
    • Raw pT, eta distribution of e+,e- daughters
    • Accepted pT, eta distribution of e+,e- daughters
    • Comparison plots between single-electron embedding, Upsilon embedding

Upsilon Paper: pp, d+Au, Au+Au

 Page to collect the information for the Upsilon paper based on the analysis of

Anthony (4/24):

in data, the electrons were selected via 0<nSigE<3, R<0.02. For pt<5, we fit to 0<adc<303. For pt>5, 303<adc<1000.

In embedding, the only selections are the p range, R<0.02, and eleAcceptTrack. The embedding pt distro was reweighted to match the data.

 

Anthony (4/5): Added new Raa plot with comparison to strickland's supression models

 

Anthony (4/4): I attached some dAu cross section plots on this page. The eps versions are on nuclear. The cross sections are as follows:

all: 25.9±4.0 nb

0-2: 1.8±1.7 nb

2-4: 10.9±2.9 nb

4-6. 5.2±5.3 nb

6-8: 0.57±0.59 nb

I expect the cross sections to change once I get new efficiences from embedding, but not by a whole lot.

 

Drew (4/6): Got Kurt's new lineshapes, efficiencies, and double-ERF parameters today. Uploading the fits to them. I'm not sure I believe the fits...

Bin-by-Bin Counting Cross Section by pT (GeV/c):

|y|<1.0 all: 134.6 ± 10.6 pb

0-2: 27.6 ± 6.3 pb
2-4: 39.1 ± 5.8 pb
4-6: 19.9 ± 3.8 pb
6-8: 13.6 ± 5.1 pb

|y|<0.5 all: 119.2 ± 12.4 pb

0-2: 23.8 ± 6.8 pb
2-4: 35.9 ± 7.4 pb
4-6: 19.0 ± 4.5 pb
6-8: 14.2 ± 4.6 pb

The double ERF is a turn-off from the L2 trigger's mass cut. Kurt used the form: ( {erf*[(m-p1)/p2]+1}*{erf*[(p3-m)/p4]+1} )/2, but I used /4 in the actual fit because each ERF can be at most 2. By fits are also half a bin shifted from Tony's, we'll need to agree on it at some point. The |y|<1 are divided by 2 units in rapidity, and the |y|<0.5 by 1 unit.

Upsilon pp, dAu, AuAu Paper Documents

 This page is for collecting the following documents related to the Upsilon pp (2009), dAu (2008) and AuAu (2010) paper:

  • Paper Proposal (Most Recent: Version 3)
  • New in v3: Now says we're going for PLB and has the E772 and MC plots included. Also has |y|<1.0 results
  • Technical Note (Most Recent: Version 6)
  • New in v3: AuAu consistency analysis and expanded summary table
  • New in v4: Added JPsi study of linewidth and 1S numbers
  •         New in v6 : Final version for paper as resubmitted to PLB
  • Paper Draft (Latest: Version 25)
  • New in v26: Updated with changes made in PLB proof
  • v25-resub: Version as re-submitted to PLB (no line numbers).
  • New in v25: Updated acknowledgements.
  • New in v24: Minor changes to discussion or TPC misalignment
  • New in v23.1: Added systematics to Fig. 3
  • New in v23: Updated with comments from Lanny and Thomas. Changes are in red.
  • New in v22: Made changed based on GPC responses to our responses to the referees. Also, all Tables are now correct. Changes are in blue.
  • New in v21: Changed in response to PLB referee comments. Changed results to likelihood fits. Added binding energy plot. Tabs. II and III are NOT correct.
  • New in v20: ???
  • New in v19: Updated with minor comments from Thomas on Nov 25.
  • New in v18: Incorporated lost changes from v16. Added 3 UC Davis undergrads to the author list.
  • New in v17: A few more changes from GPC comments and addition of AuAu cross sections
  • New in v16: Changes from GPC comments after collaboration review
  • New in v15: Collaboration review changes
  • New in v14: English QA changes
  • New in v13: Mostly minor edits suggested by Lanny and Thomas
  • New in v12: Updated the MC section to addredd |y|<0.5. Also did some other, minor graphwork on fig 3b
  • New in v11: Updated with latest comments from the GPC. Official version before the first GPC meeting
  • New in v10: Updated from PWG discussion. Cleaned and enchanced plots
  • New in v9: Cleaned up v8
  • New in v8: Added analysis of 1S state and discussion of E772
  • New in v7: Made many changes based on first round of GPC e-mails. Summaries of changes and responses can be found on the responses sub-page.
  • New in v6: Cleaned up most plots. Reworded end of intro. Cleaned up triggering threshold discussion. Added labels for subfigures.
  • New in v5.1: Made stylistic clarifications and fixed a few typos. Updated dAu mass spectrum legend to explain grey curve.
  • New in v5: PLB formatting and some plot clean-up
  • New in v4: E772 results and |y|<1.0 and |y|<0.5 both included for AuAu

 

Responses to Collaboration comments

Thanks to all the people who submitted comments. These have helped to improve the draft.  Please find the responses to the comments below.

Comments from JINR (Stanislav Vokal)

1) Page 3, line 40, „The cross section for bottomonium production is smaller than that of charmonium [8-10]...“, check it, is there any cross section for bottomonium production in these papers?

Answer: Both papers report a quarkonium result.  The PHENIX papers quote a J/psi cross section of ~178 nb. Our paper from the 2006 data quotes the Upsilon cross section at 114 pb. 

2) Page 3, lines 51-52, „compared to s_ccbar approx 550 - 1400 mb [13, 14]). ...“. It should be checked, in [13] s is about 0.30 mb and in [14], Tab.VII, s is about 0.551 – 0.633 mb.“.

Answer: In Ref. 13, the 0.3 mb is for dsigma/dy, not for sigma_cc.  To obtain sigma_cc, one has to use a multiplicative factor of 4.7 that was obtained from simulations (Pythia), as stated in that reference.  This gives a cross section of ~ 1.4 mb, which is the upper value we quote (1400 \mu b). In reference 14, in Table VIII the low value of 550 \mu b is the lower value we use in the paper.  So both numbers we quote are consistent with the numbers from those two references.

3) Page 3, line 78, „...2009 (p+p)...“ and line 80 „20.0 pb-1... “, In Ref. [10] the pp data taken during 2006 were used, 7.9 pb-1, it seems that this data sample was not included in the present analysis. Am I true? If yes – please explain, why? If the data from 2006 are included in the present draft, then add such information in the text, please.

Answer: That is correct: the data from 2006 was not included in the present analysis.  There were two major differences.  The first difference is the amount of inner material. In 2006 (and 2007), the SVT was still in STAR. In 2008, 2009, and 2010, which are the runs we are discussing in this paper, there was no SVT. This makes the inner material different in 2006 compared to 2009, but it is kept the same in the entire paper.  This is the major difference. The inner material has a huge effect on electrons because of bremsstrahlung, and this distorts the line shape of the Upsilons.  The second difference is that the trigger in 2006 was different than in 2009. This difference in triggers is not insurmountable, but given the difference in the amount of inner material, it was not worth to try to join the two datasets. We have added a comment to the text about this:

"All three datasets were taken with the same detector configuration.
Note that the data from our previous pp result was not added to this analysis because the
amount of material in the detector was different during 2006 than in all the three datasets discussed here, preventing a uniform data analysis."

4) Page 4, Fig.1, numbers on the y-axe should be checked, because in [10], Fig.10, are practically the same acounts, but the statistic is 3 times smaller;

Answer: The number that matters is the counts in the Upsilon signal.  In Fig. 10 of Ref. 10, there is a lot more combinatorial background (because of the aforementioned issue with the inner material), so when looking at the total counts one sees a similar number than in the present paper. However, in the case of the 2006 data, most of the counts are from background.  The actual signal counts in the highest bin of the 2006 data are ~55-30 = 25, whereas the signal counts in the present paper are ~ 50 - 5 = 45 in the highest bin. When you also notice that the 2006 plot had bins that were 0.5 GeV/c^2 wide, compared to the narrower bins of 0.2 GeV/c^2 we are using in Figure 1 (a), it should now be clear that the 2009 data has indeed more statistics.

5) Page 5, line 31, „114 ± 38+23-14 pb [10]“, value 14 should 24;

Answer: Correct. We have fixed this typo. Thank you.

6) Page 5, Fig.2, yee and yY should be identical;

Answer: We will fix the figures to use one symbol for the rapidity of the upsilons throughout the paper.

7) Page 5, Fig.2 – description, „Results obtained by PHENIX are shown as filled tri-angles.“ à diamond;

Answer: Fixed.

8) Page 6, Fig.3a, here should be hollow star for STAR 1S (dAu) as it is in Fig.3b;

Answer: Fixed.

9) Page 8, line 7, „we find RAA(1S) = 0.44 ± ...“ à should be 0.54;

Answer: Fixed.

10) Page 8, lines 9-12, „The ratio of RAA(1S) to RAA(1S+2S+3S) is consistent with an RAA(2S+3S) approximately equal to zero, as can be seen by examining the mass range 10-11 GeV/c2 in Fig. 4.“, it is not clear, check this phrase, please;

Answer: We have modified this phrase to the following: "If 2S+3S states were completely dissociated in Au+Au collisions, then R_AA(1S+2S+3S) would be approximately equal to $R_AA(1S) \times 0.69$.  This is consistent with our observed R_AA values, and can also be inferred 

by examining the mass range 10--11 GeV/c^2 in Fig. 4, 
where no significant 2S or 3S signals are seen." 

11) Page 8, line 26, „CNM“, it means Cold Nuclear Matter suppression? – should be explained in text; 

Answer: The explanation of the CNM acronym is now done in the Introduction.

12) Page 9, line 30-31, „The cross section in d+Au collisions is found to be = 22 ± 3(stat. + fit)+4- 3(syst.) nb.“, but there is no such results in the draft before;

Answer: This result is now given in the same paragraph where the corresponding pp cross section is first 
stated, right after the description of Figure 1.

13) Page 9, line 34, „0.08(p+p syst.).“ à „0.07(p+p syst.).“, see p.7;

Answer: Fixed. It was 0.08

14) Page 10, Ref [22], should be added: Eur. Phys. J C73, 2427 (2013);

Answer: We added the published bibliography information to Ref [22].

15) Page 10,, Ref [33] is missing in the draft.

Answer: We have now removed it. It was left over from a previous version of the draft which included text that has since been deleted.

Comments from Tsinghua

1) Replace 'Upsilon' in the title and text with the Greek symbol.

Answer: Done.

2) use the hyphen consistently across the whole paper, for example, sometimes you use 'cold-nulcear matter', and at another place 'cold-nuclear-matter'. Another example is 'mid-rapidity', 'mid rapidity', 'midrapidity'...

Answer: On the hyphenation, if the words are used as an adjectivial phrase, then those need to be hyphenated.  In the phrase "the cold-nuclear-matter effects were observed", the words "cold-nuclear-matter" are modifying
the word "effects", so they are hyphenated. However, from a previous comment we decided to use the acronym "CNM" for "cold-nuclear matter", which avoids the hyphenation.  We now use "mid-rapidity" throughout the paper.

3) For all references, remove the 'arxiv' information if the paper has been published.

Answer: We saw that published papers in PLB do include the arxiv information in their list of references. For the moment, we prefer to keep it there since not all papers are freely available online, but arxiv manuscripts are. We will leave the final word to the journal, if the editors ask us to remove it, then we will do so.

4) Ref. [33] is not cited in the text. For CMS, the latest paper could be added, PRL 109, 222301 (2012).

Answer: Ref [33] was removed. Added the Ref. to the latest CMS paper on Upsilon suppression.

5) For the model comparisons, you may also compare with another QGP suppression model, Y. Liu, et al., PLB 697, 32-36 (2011)

Answer: This model is now included in the draft too, and plotted for comparison to our data in Fig. 5c.

6) page 3, line 15, you may add a reference to lattice calculations for Tc ~ 175 MeV.

Answer: Added a reference to hep-lat/0305025.

7) Fig 1a, \sqrt{s_{NN}} -> \sqrt{s}. In the caption, |y| -> |y_{ee}|

Answer: Fixed.

8) For the dAu rapidity, the directions of Au-going and p-going should be explicitly defined.

Answer: We also realized that this was important to do. This is now done by adding the sentence: "Throughout this paper, the positive rapidity region is the deuteron-going direction, and the
negative rapidity region is the Au-going direction. "

9) Fig.2a, the label of x-axis, 'y_{ee}' -> 'y_{\Upsilon}'. In the caption for Fig. 2a, Ref. [21] should be cited after 'EPS09 nPDF'.

Answer: We moved the citation to the first part of the caption.

10) page 5, around line 28-29, please mention explicitly this result is for p+p 200 GeV.

Answer: Done. The text now reads "we calculate a production cross section in p+p collisions..."

11) page 7, line 33, add space after N_{part}

Answer: Fixed.

12) page 7, line 36, Fig. 5c -> Figure 5c

Answer: Done.

13) page 7, line 46, remove 'bin from'

Answer: Done.

14) page 7, line 55, 'the latter' -> 'the former' ?

Answer: Split the sentence into two, and explicitly stated "The level of suppression we observe for
|y|<0.5 stays approximately constant from dAu up to central AuAu collisions. " to make it clear.

15) Fig. 4 a, b, and c, '30%-60%' -> 30-60%, '10%-30%' -> '10-30%', '0%-10%' -> '0-10%' In the caption, |y| -> |y_{ee}|

Answer: Fixed.

16) Fig. 5, the label of the y axis better to be the same style as Fig. 2

Answer: Fixed.

17) Page 9, line 33, line 45, when quoting the RdAu and RAA, why omit the p+p stat. errors? Also the p+p syst. err. in line 34 is not the same as that in page 7, line 41, please check.

Answer: The p+p stat. errors are combined together with the Au+Au stat. errors because it is straightforward to combine stat. errors, and we just quote the combined stat. error. Syst errors are fixed.

Comments from UCLA

1. In the legends of Fig 1 and Fig 4, the line color for the like-sign and unlike-sign should be blue and red, instead of black.

Answer: Fixed.

2. On page 5, line 29, it is not specified whether this is for p+p or dAu.

Answer: Done. The text now reads "we calculate a production cross section in p+p collisions..."

3. The directions of the d and Au beams were not defined: which goes forward and which backward in y? It will be good to specifiy the direction, and briefly discuss the different physics we expect from the forward and backward regions.

Answer: We also realized that this was important to do. This is now done by adding the sentence: "Throughout this paper, the positive rapidity region is the deuteron-going direction, and the
negative rapidity region is the Au-going direction. "

4. Page 7, line 50, "Pb+Pb" should be upright.

Answer: Done.

5. Page 7, line 55-56, "the latter" should be the model, which doesn't look constant. It seems you are talking about the measurements. Then it should be "the former".

Answer: Split the sentence into two, and explicitly stated "The level of suppression we observe for
|y|<0.5 stays approximately constant from dAu up to central AuAu collisions. " to make it clear.

6. Page 8, line 13-14, "in d+Au to be $2\sigma$ from unity and consistent with unity in peripheral" -> "to be $2\sigma$ from unity in d+Au and consistent with unity in peripheral"

Answer: Done.

7. Page 8, line 22, "modeling"

Answer: There are two aims: to incorporate... and to model ... Since we use the infinitive form in the description of the first aim ("to incorporate") we also use the infinitive form ("to model") in the second aim.

8. Page 3, line 82, "pQCD" -> "perturbative QCD (pQCD)"
9. Page 5, line 6, "perturbative QCD" -> "pQCD"

Answer: Both are now fixed.

10. Page 5, Fig 2, the caption says "Results obtained by PHENIX are shown as filled triangles", but they are "diamonds", not triangles in figure.

Answer: Fixed.

11. Pg 4 Line 1 : Barrel Electro-Magnetic Calorimeter (EMC) - Barrel Electro-Magnetic Calorimeter (BEMC) and replace EMC with BEMC throughout.

Answer: Done.

12. Pg 4 Line 65 : |y_{\upsilon}| - |y|. In the following Figure 1, its |y_{ee}| < 0.5 in figure panels and |y| < 0.5 in caption. Inconsistency, if all of them are same.

Answer: Fixed.

13. Pg 5 Line 1 : The data are fit .. - The data are fitted ..

Answer: Both forms are grammatically correct. The past participle can be either "fit" or "fitted".
http://en.wiktionary.org/wiki/fit#Verb
We kept the text as is.

14. Pg 5 Line 6 : via a perturbative (pQCD) next to leading order (NLO) - via a next to leading order (NLO) pQCD

Answer: Done.

15. Pg 5 Line 41 : ... with respect to ... - ... with respect to the ...

Answer: It is correct as written, usage: with respect to (something). One could also use "with respect to the" but then we would need to add another noun, for example as in, "with respect to the binary-collision-scaling expectation". We felt the original form was ok.

16. Pg 5 Line 46 : ... yield ... - ... yields ...

Answer: Done.

17. Pg 6 Line 25 : The present data ... - The present data in which figure ?

Answer: It is now made clear in the text that this refers to Figure 2b.

18. Pg 6 Caption for Fig. 3 : Use a) and b) instead of top and bottom

Answer: Done.

19. Pg 6 Caption for Fig. 3 : x_{F} in caption and X_{F} in figure  

Answer: Fixed.

20. Pg 8 Line 26 : when CNM first appears, it needs to be spelled out.

Answer: Done, it is now given in the Introduction.

21. Pg 9 Line 28 & 31 : The term B_{ee} \times is missing in front of d\sigma/dy

Answer: Done. 

Comments from Creighton

Page 3, Line 71. Why only p+p and d+Au? Why is the Au+Au cross-section not extracted?

Answer: We typically extract the yield per event in AA. This can be transformed into a cross section if we use the integrated luminosity. To get from a total number of minimum-bias events to an integrated luminosity all that is needed is the hadronic cross section for AuAu collisions, which is typically obtained using a Glauber model.  We typically don't quote it mainly because what the community wants to know is R_AA itself.  That is the quantity that the theorists typically calculate, and so we had received guidance to not include a cross section. (It was actually included in earlier versions of the draft.) Given this call for including it, we have now brought it back to the draft.

Figure 2. It might be more appropriate to include the description of the symbols in the figure caption rather than in the text. The legend might be reformatted so the description of symbols has the same structure for STAR, PHENIX, and Ramona Vogt. Why not use a consistent label for what we understand to be the same quantity expressed on the horizontal axis? (Figure 2a uses the rapidity for e+e- while Figure 2b uses rapidity for the upsilon.)

Answer: The caption now describes the symbols too. We left the description in the text also, to help the reader. 

Page 5, Line 4. The wording in the text makes it sound like the red line in Figure 2 could refer exclusively to the upsilon production.

Answer: We have reworded this part to:
"The data are fit with a parameterization consisting of the sum of various contributions to the

electron-pair invariant-mass spectrum. The lines in
Fig. 1 show the yield from the combinatorial background (dashed blue line), 
the result of adding 
the physics background from Drell-Yan and \bbbar\ pairs
(dot-dashed green line), and finally the inclusion of the \upsi\ contribution 
(solid red line)."

Page 6, Line 18. It might be more appropriate to discuss here why the mid-rapidity point is lower than the prediction (rather than later in the text).

Answer: In a sense, the next paragraphs and figures are meant to discuss this point being low. We use R_dAu to have more discussion of the model predictions (and show their uncertainties). We next compare our result to previous measurements, which show a similar suppression.  We added the sentence "To study this observation for \dAu\ further, we make a closer comparison to models and to previous measurements of \upsi\ production in p+A collisions. " to highlight this.

Page 7, Line 11/Figure 3b. It is unclear how the plot in terms of Feynman-x improves the comparison of rapidity coverage.

Answer: We added the x_F plot because the E772 data were given in x_F. We can massage our data to get x_F from rapidity making some estimates about the pT, which we can do because we have all the information on the Upsilon 4-momenta for our data, but we do not have this information for E772. So in order to compare to their result, it was best to not touch their data and massage ours, with intimate knowledge of ours, than to keep everything in y_Upsilon but having to massage their data without knowledge of their pT distribution so that we would only be guessing as to the correct y_Upsilon that would correspond to a particular x_F range.

Page 9, Line 30. This result in the conclusions does not seem to have been presented in the body of the paper.

Answer: This result is now given in the same paragraph where the corresponding pp cross section is first 
stated, right after the description of Figure 1.

Comments from WUT

Reader 1:
1. legend of Fig. 1b
--------------------
I would rather put R_{dA}=1 (not R_{AA}) to be consistent with the figure caption and the main text

Answer: Fixed.

2. Fig 2a and discussion in the text
of the results for pp at positive and negative rapidities.
----------------------------------------------------------
I found it a bit awkward that we are presenting results just after folding in data at positive and negative y.
Of course the physics for pp is symmetric wrt y=0,
but it would be better to present separately results
for -1 < y < -0.5 and 0.5 < y < 1.0 to show that indeed the results are consistent.
(Also as a cross check of correctness of including all experimental corrections, and nothing to hide)

Answer: We did check that the results were consistent for pp, but we wanted to maximize the statistical power of the data, given that we are still somewhat statistics limited.  Note that the acceptance and efficiency is lower for the 0.5 < |y|< 1.0 region, so that is why we wanted to add the two in pp, thanks to the symmetry, to show our best results.  For the d+Au case, as we say in the paper, we did leave the analysis in distinct rapidity regions because the system is not symmetric.

3. legend of Fig. 2a
--------------------
For STAR and PHENIX points it would be more transparent,
if the legend would have similar layout as for NLO pQCD CEM.
I.e. 'STAR' in a single line followed by two lines
'pp' and 'dAu/1000' and analogously for
PHENIX/

Answer: Fixed.

4. line 2 on page 7
------------------
"their deuterium result" => "their pd result"
would be more straightward statement
(I assume E772 had a liquid deuterium target to study pd collisions)

Answer: Done. And yes, we say in the text that they had a liquid deuterium target.

5. Fig. 4
---------
The curves for combinatorial background should be made smooth
like for all other curves, not going in steps.

Answer: Fixed.

Reader 2:
page 4, line 1 and in further occurences: shouldn't it be BEMC instead of EMC ?
--------------------
Answer: Done.

page 5, line 1: shouldn't it be "The data are fitted"
---------------------------------------
Answer: Both forms are grammatically correct. The past participle can be either "fit" or "fitted". 
http://en.wiktionary.org/wiki/fit#Verb
We kept the text as is.

Reader 3:
Overall it is a very well written paper and important results.

1. Acronyms in the introduction should be defined there (RHIC, LHC, pQCD or even QCD)
--------------------

Answer: Done.

p. 3, l. 60: you use "cold-nuclear-matter effects" without defining what "cold" and "hot" nuclear matter is. It would be good to introduce these terms when you talk about QGP and then other possible sources of suppression (line 52-63)
--------------------

Answer: Added short phrases to better define these terms.

p.8 l.26 - CNM should be defined
--------------------

Answer: It is now defined in the Introduction.

p.8 l.44-48 - it is not clear from the text how exactly CNM and QGP effects were combined for the scenario 4.
--------------------

Answer: We now state "For scenario 4), the expected suppression is simply taken to be the product of the suppression from scenario 2) and scenario 3)."

p.9 l.29 "with NLO" -> with "pQCD NLO"
--------------------

Answer:  In the rest of the paper, we have used NLO pQCD, so at this point, it should be clear that when we are talking about
a Next-to-Leading Order calculation, we are implicitly talking about a perturbative QCD calculation (the fact that we are talking
about "orders" in a calculation implies 
that we are talking about perturbation theory,
and this entire paper deals with QCD), so it should be clear from the context.

Figures: Caption of Fig 2: " from EPS09 with shadowing" - "EPS09" is nPDF which includes shadowing already, maybe write "due to shadowing using EPS09"?
--------------------

Answer: Changed the caption so it reads: "The dAu 

prediction uses the EPS09 nPDF which includes shadowing"

Fig 2 and Fig 6 - the contrast of the figures could be improved - for instance lines for models in Fig. 2 are barely visible when printed in black and white

Answer: Fixed.

Reader 4: Fig. 1 and Fig 4 - The information on pT range,
in which the signal is presented, can be added.
-------------------------------------

Answer: We added a sentence at the end of the "Experimental Methods" section to state: "For all results we quote, the Upsilon data are integrated over all transverse momenta."

Comments from BNL

The new p+p result is significant, why is it not in title?

Answer: We already have one paper that is all about the pp cross section. Our result in this paper is an improvement, but the new results on suppression are the highlight of the paper, and we felt they deserved to be emphasized in the title.  If we change the title to something like "Upsilon production in pp, d+Au, and Au+Au collisions at sqrt(s_NN) = 200 GeV" would include the pp result in the title, but it will not mention suppression.  We prefer to emphasize the suppression, as that is the new, important result. Since we are attempting to publish in Physics Letters B, we felt it was more appropriate.

The paper is not clear in many places, and would be helped from a re-­write keeping the audience in mind, i.e. not nesc. an expert in HI.  It was commented that in particular the introduction on page 2 line 56 to 66 has much expert knowledge assumed, but does cover the field. Some examples are given below in the individual comments.

Answer: We tried to make the introduction section a short review of the field so that a non-expert could follow.  We don't understand which expert knowledge is assumed in the introduction in lines 56-66.  We certainly have strived to make the paper clear, and we will look for the specific comments and suggestions below.

The different RAA values appears multiple places in text. We think it is important to present these in tabular form, particular since so many numbers are presented RAA |y| <0.5, 1 centrality and collision system. Noted by several readers. Page 7,30-­‐50 Page 8, 4-­‐20

Answer: A table with all the values has now been added to the paper.

The definition of RAA seems a bit colloquial, normally this is defined vs. e.g pt, but in the case of the Upsilon it is our understanding this is an integral of the cross section over all (or some) pt-­‐range divided by the pp . The paper should define this clearly.

Answer: We specifically wrote in the paper the equation used for R_AA.  This is as clear a definition as we can make.  We also now specify that our measurements are integrated over all pt.  

The abstract should reflect the conclusion of the paper, this does not at present.

Answer: The abstract includes the most central R_AA and the R_dAu values, which are some of the most important results of the paper.  We also state three of the most important conclusions we draw from the data:

Our results are consistent with complete suppression of excited-state Υ mesons in Au+Au collisions. The additional suppression in Au+Au is consistent with the level expected in model calculations that include the presence of a hot, deconfined Quark-Gluon Plasma. However, understanding the effects seen in d+Au is still needed before fully interpreting the Au+Au results.

 The most important observation, which is the unexpected observation that R_dAu is the same as R_AA for central events in the |y|<0.5 region, is the reason why we wrote the last sentence in the abstract.

 
The paper needs clarification in regard to the material budgets for the 3 running periods. The text alludes to differences, e.g. how its included in the fits. Why not summarize the rad lengths for pp, dAu and AuAu to be precise. If not, it is very hard to follow the different figures, and clearly different response functions for the Upsilon peaks.
Answer: This is now fixed. The sentence in question alluded to differences in the material budget, but for the three years there were no differences in the material budget. Only the differences in the detector occupancy and the detector calibrations affect the width.  In the new version, we also mention explicitly that the 3 running periods have the same material budget.
Page 6 Please define XF, how you used XF. It was not found in the analysis note, and we have problems to understand how we can reach XF~0.4 when measuring at mid-­‐ rapidity Xf= pz/pzmax normally, so are we seeing Upsilons with Pz=40 Gev in y<1? In any case its not defined.

Answer: Good catch! We made a mistake in the calculation for STAR, we accidentaly used the E772 value for the beam momentum. We were originally thinking of transforming their values of x_F to rapidity, but then when we decided not to move their data and change ours to x_F, we did not use our value for the beam momentum.  The figure is updated.  But the most important point which is at y=0 remains at x_F=0, so the comparison to the level of suppression seen by STAR and E772 at x_F=0 stays the same.
 
On page 8 line 7 it say RAA = 0.44+-­‐… where as figure 5 c clear as R > 0.5. Please clarify.

Answer: It should be 0.54, it was a typo, and is now fixed.
 
The discussion between the |y|<1 and |y|<0.5 is not clear cut, particular for the AuAu; It is surprising to have such difference. Is it possible this reflects un-­accounted systematic error or is it all statistical? It does take away from the final conclusions since for |y|<0.5 there is no suppression relative to dAu where as there is for |y|<1. This clearly translates into the interpretation of the interesting model comparisons presented in fig 6. Conclusions in the text are iffy. The data in fig 5 as given do NOT indicate any (significant) centrality dependence vs. Npart , only for RAA(1S). Is that the message that should come across?

Answer: We have discussed the differences in the |y|<1 and |y|<0.5 in the PWG, precisely to try to make sure that the results we are observing in |y|<1 and in |y|<0.5 are statistically consistent.  One of the results is a subset of the other, so one must be careful to take into account the correlations.  This study is in the technical note, in section 6A (page 33).  We concluded that the results are self consistent.  As to whether the result is statistical fluctuation, this is a possibility, but that is the case for any result, and the only way to remedy that situation is to run more dAu.  As to whether it could be a systematic effect, we have done the analysis in |y|<0.5, in |y|<1, and in 0.5<|y|<1 where for each we use the same methods for extracting the signal, for applying efficiency and acceptance corrections, for estimating the backgrounds, etc.  So if there is a systematic effect, it would affect the |y|<0.5 and the 0.5<|y|<1 region in the same way, and therefore it would not lead to differences between these two regions.  We do not think that this "takes away" from the final conclusions, because it is an observation that is not expected if there should be binary scaling in dAu, and it makes the result more interesting.  The reason why we included the E772 data was precisely because we observed such a striking suppression in dAu. So indeed, the fact that the data in Fig. 5b do not show a significant centrality dependence vs. Npart is one of the most important observations of the paper. And with the E772 data, we can point to a previous result that shows a similar level of suppression in pA.  Therefore, this paper will serve to exhort the community to take a closer look at Upsilon suppression in pA or dA.  We do not understand the comment about conclusions being "iffy". If there is a specific conclusion that does not seem to be supported by the data, then we can address that. 

The last sentence in conclusion seem exaggerated, and not documented from text just remove.

Answer: One of the main points of the paper is that in Fig. 5b, as we explain in the previous answer, there is no evidence for a significant centrality dependence of Upsilon suppression in dAu.  The models predict the level of suppression we see in AuAu, but one of the key results of the paper is the suppression seen in dAu. The GPC strongly advocated to include a sentence in the conclusions of the paper that cautions readers that one must understand the dAu suppression before any strong claims can be made. The last sentence was rephrased slighly to better reflect this.  

In abstract suggest the remove the sentence “Our measurements p+p…” and add to the text where relevant in the introduction. Not really relevant.

Answer: Done.

Individual comments:

Page 3 line 34: it is not at all obvious how the 2 statements (deconfinement and high temperature phase of lattice QCD where color is an active degree of freedom) in this sentence are scientifically connected.

Answer: The connection is that color Debye screening, which is the original effect proposed by Matsui and Satz,
requires a quark-gluon plasma where the color charges of the high-temperature plasma screen the heavy-quark potential that binds the bottomonium (or charmonium) states.  This is one of the key ideas in QGP physics.

Page 3 line 59 for a non HI guru this argumentation is basically impossible to follow. Also ccbar and bbar pairs are produced the same way through gg fusion so why should there be a difference.

Answer: It seems that the question arises because the inquirer did not follow that the arguments presented are about final state effects, since the comment about ccbar and b-bbar pairs being produced through gluon fusion is about their production in the inital state, not about the possible ways that they can be broken up in the final state.  The comment about 
the interaction cross section of the Upsilon with hadrons applies to the final state, once the hadrons are produced.  The size of the upsilon meson is much smaller than the J/psi meson, and the corresponding cross section of an Upsilon to interact with a final state pion (and then break up into a pair of B mesons) is much smaller than the cross section for a J/psi to be broken up by a pion into a pair of D mesons.  We will add a comment that the effects discussed in this section are final state effects.

Page 3 line 46. There is no reference to statistical recombination.

Answer: Added a reference to Thews et al.

Page 3 line 78 there is no issues using the 2008 dAu data even so other analysis claim they cannot publish because of the non perfect tpc alignment?

Answer: We put a lot of work to take into account the effect of the TPC misalignment.  This is discussed in the Technical Note in Section V.F, page 29. In particular, the 2009 pp data was originally processed with the same misalignment that the 2008 dAu data and the 2010 AuAu data both have.  The 2009 pp data was subsequently reprocessed with fixed calibrations, and we studied the effect that the distortions had on our invariant mass reconstruction on an event-by-event basis, i.e. comparing the mass obtained in the production with the misalignment and then with the misalignment fixed on the exact same event.  This allowed us to characterize the effect of the misalignment and to take it into account in embedding for the line-shapes and then in the extraction of the Upsilon yield via the fits using those line-shapes.  This was studied extensively in the PWG in large part because we wanted to make sure that any issues regarding the misalignment would be dealt with appropriately.  We cannot comment on other analyses, but if they can also study the differences in the two pp 2009 productions, that could help them to account for the TPC misalignment in their own analyses.

Fig 1 caption – comment to fit: the chi^2 of the pp fit must be horrible, any reason why the fit does not describe the data better.

Answer: The chi^2/NDF is 1.37 in the pp fit.  This is not something we would characterize as "horrible".  Given the statistics, there is not a strong reason to change the fit from using components we expect to have, namely the Upsilon states, the Drell-Yan and b-bbar continuum, and the combinatorial background.

2nd question: was the setup of STAR, especially the material budget, the same? If not, which I assume, how different are they?

Answer: The material budget was the same.  The TPC misalignment in dAu, and AuAu increases the width compared to pp. The higher occupancy in AuAu also contributes to a broadening compared to pp.  As noted above, we now explicitly state
in the paper that the material budget in all three datasets is the same.

page 5 line 6 (fig caption) ‘band’ -> box/square

Answer: The NLO calculations are shown as a band, and that is what is mentioned in the caption.

page 6 line 48: the effect at mid rapidity taking the systematic uncertainty into account is 2 sigma max. I think this is a number which needs to be stated.

Answer: We state the value of R_dAu with statistic and systematic uncertainties. We will also provide a table with all the R_AA and R_dAu values. The sentence we use in page 6 line 48 says that the suppresion is "indicative" of effects beyond shadowing, initial-state parton energy loss, or absorption by spectator nucleons.
Using "indicative" is usually warranted for effects that are of ~2 to 3 sigma significance, we certainly not claim a "discovery" (5sigma). 

Itʼs a bit hard to follow the various R_AA and R_dAu quoted in the paper. A table listing the R_{AB} for the various combinations might be more useful than scattering the values through the text.

Answer: A table is now provided.

Abstract: I realize that in the abstract you donʼt want to get too technical, but omitting the rapidity range and whether it is 1S or 1S+2S+3S makes the numbers not useful.

Answer: We added a short clarification in the abstract as to the result quoted being 1S+2S+3S, and in the rapidity range |y|<1.

p. 4: Lines 55-57: the tracking and electron identification efficiencies would be the same across the three datasets, but in the previous paragraph there was discussion about differences in efficiency. Needs to be made clearer.

Answer: The text is now clear that the main thing that was chosen to be the same was the electron identification efficiency.

Fig1 The N_{--} is unclear the – runs together with the N

Answer: Fixed

Fig. 2: Vogt band does not print well.

Answer: Increased the line weights and changed the colors to darken them so that they print better.

fig 2a needs ""Phenix"" in dAu/1000 (open diamonds)

Answer: Fixed

Fig 2: “are shown as triangles There are no triangles,

Answer: Done. It should be diamonds.

c) Fig 3a The label A^0.96 is not the actual black curve which is (A/2)^{-0.04) according" "to the text in pg 7. Maybe writting the A^{alpha} scaling of cross section in the figure may help.

Answer: Fixed

in Fig 4 where the CB in all three panels is not a smooth curve nor a histogram; it has an unusual "mexican pyramid" shape

Answer: What's wrong with Mexican pyramids? :-) The plot will now be a smooth curve.

The A to the 0.96 does not match the text in line 5 page 7

Answer: As noted above, the Figure will now display A^0.96 scaling to make clear that the line shown is not A^0.9, but 
rather derived from a cross section that scales as A^0.96.

Fig. 5: Are the shaded boxes systematics in the AB system? If so, needs to be in the caption.

Answer: Fixed

Fig. 6: "Our data is shown as a red vertical line with systematics shown by the pink box. There are two systematics (pp and AB). What was done with these? The pp is common to d+Au and Au+Au, so not clear, actually, what should be done.

Answer: The two systematics were added in quadrature for Fig. 6, we now state that in the paper. (Agree that it is debatable how to best combine them, but we should state what was done.)

.p. 6, lines 43-44: Do you mean y<~-1.2, rather than 1.2? Otherwise the argument doesnʼt make sense. And, where is the 1.2 from (citation)?

Answer: Correct, it should be -1.2.  We do give the reference (23) for this statement in the previous sentence.

p. 8, line 11: consistent with an RAA(2S+3S) approximately equal to zero. Would be better to quantify this as an upper limit. 

Answer: This section was reworded based on suggestions from another reader. The argument now starts with the hypothesis of an approximately zero yield of the 2S+3S, states what that would imply for the R_AA(1S) and R_AA(1S+2S+3S) values, and 
then notes that this is consistent with our data.

p. 9, line 1: at how many sigma was the exclusion? At 4.2 sigma, as quoted later?

Answer: The exclusion the "no-suppression" scenario had a p-value of less than 1 in 10^7 (better than 5 sigma) for all R_AA cases in AuAu. The R_dAu had a different p-value of 1.8 * 10^-5 (~4.2 sigma).

Line 18: result rather than effect reads better.

Answer: Done.

How were systematics taken into account in the quoting of “sigma”?"

Answer: The only time we quote "sigma" are for the exclusion of the "no-suppression" scenarios.  For R_AA, they would still
be excluded at better than ~5 sigma even including systematics.  For the dAu case, if the p-value is calculated with the systematic uncertainty shift we get 1.5 x 10^-3, which is about 3sigma.

a) The style of the paper is too colloquial for my taste, but I'm told that journals have relaxed their style requirements.

Answer: This is a style issue, we are certainly willing to discuss this with the editors of the journal if need be.

d) Reference [10] explains that the Combinatorial background is obtained by fitting the same charge sign pair distribution and that appears to be the case in this paper except in Fig 4 where the CB in all three panels is not a smooth curve nor a histogram; it has an unusual ""mexican pyramid"" shape.

Answer: The plots will all have a smooth curve.

Page 7 top (line)9 From the figs its not obvious there is 4.2 deviation, more like 3, can you cross check.

Answer: See previous comments on the deviations and statistical significance.

Clearly the difference between y 0.5 and 1.0 make the conclusion a bit waffly.

Answer: For dAu, in both scenarios we are excluding the no-suppression scenario. Both datasets are supporting this conclusion. Furthermore, the comment we make in about a 4.2sigma exclusion of the no-suppression scenario comes
from the |y|<1 measurement, which is the weaker exclusion of the two. The |y|<0.5 only serves to make this conclusion stronger.

The notation and fonts for RAA and Upsilon(1S+2S+3s) not not consistent across paper.
Answer: plots are now consistent (For Anthony).

Page 8 line 48 “ assumed a flat prior..” This reference to statistics may or may not come across well to the general reader,
Possible expand on this.

Answer: We have followed other papers in the Physics Letters B which use these same statistical techniques, and this usage was accepted.

One minor comment:" "In Fig.6, “CMN effects” should be “CNM effects”

Answer: Fixed.

Page 4 line 28&57, the three datasets” clarify to indicate “between the datasets from the three collisions systems”"

Answer: Done.

"line 57" "‘be the same” Really, should it not be “approximately the same".

Answer: Done.

Responses to GPC, April 2014

 Thomas:

1. General: with the new text (in red) there's no a wild mix
of Au in roman and italic in normal text and in super/sub-scripts. Since Au is a chemical symbol I would put it all in roman
consistently.

I fixed the remaining instances of italicized "Au"s in the text. 
2. Page 3, line 30, Sentence starting "Additionally ...".

This sentence doesn't say a lot and as I already mentioned that
I do not think the feed-down pattern is any more complex
than that in the charmomium sector. I attached a schematic
diagram. Replace Y with Psi and chi_b with chi_c and h_b with h_c
and that's it.

Why not simply saying here that the amount of feed-down into
the Y(states) is not measured at RHIC energies and then give
numbers of the next closest energy (which is Tevatron I guess).

We've changed the discussion of feed down in the introduction. We added a reference to the Tevatron results. We also discussed the direct fraction and its implication for the interpretation of the 1S results.

3. Fig 1,: I already mentioned that I suggest to turn this
into a table. The plot doesn't really provide any new insight.

Done.

4. Page 9, line 13.
"*" -> "\times" or just leave it out

Changed to \times. It helps distinguish the (1S) as an argument and the next set of parens as a mathematical expression.


5. Page 11, Line 18.

I wonder if one should add one sentence mentioning the Y suppression
in high multiplicity pp events seen by CMS. Fits in the context.

I would argue it's a little ambiguous whether we should do this. If we were citing LHC results, I think this would be prudent. However, we have yet to see evidence of Upsilon suppression (or J/Psi suppression) in pp collisions at RHIC energies.


6. Page 11, line 50.

Delete "However".

Done.


7. Fig. 6. The font size of the legend is a bit on the small side.

There's enough room to make it a tic bigger.

I've tried to squeeze a larger font in there. Thoughts?
 

8. Table II.
Can we really say that d-Au is 0-100%? That would be zero bias.
Wasn't there a min-bias mixed with the Y trigger. To my knowledge
we never quoted anything above 80/90%. What about simply saying
min. bias instead of 0-100%.

Done.



Lanny:

P3 L30 -- remove "complex" (it is an unnecessary adjective here)

OK

P4 (new) Fig.1 and red text lines 50-51, 65-69:  The efficiencies are
about the same for the 30-60, 10-30 and 0-60 at each rapidity bin.
This information probably should be in the text since HF reco. eff.
are useful to know by others in the business. I recommend putting
this information in the text in place of the above Figure 1 and lines, e.g.

   "The $\Upsilon$ acceptance $\times$ efficiency for three centrality
bins (30-60%, 10-30%, 0-60%) are XX, XX and XX for respective
rapidity bins |y|<0.5, |y|<1.0 and 0.5<|y|<1.0. For the 0-10% centrality
the corresponding total efficiencies are reduced by approximately XX%."

We removed the figure and made it a table instead.
 

Please check that the various uses of "total efficiency", "reconstruction
efficiency", "acceptance times efficiency" etc are used consistently and
avoid extra such terms if possible.

P5 Fig2b -- The legend "p+p x <Ncoll>" is misleading and may be what ref.2
is asking about. The grey band in 2b is not simply the red curve in 2a
multiplied by a constant (Ncoll).  There are resolution effects as discussed
on P6. The caption should say, "The grey band shows the expected yield if
RDAu = 1 including resolution effects (see text)."

I added your wording in the caption.
 

P5 L8 -- Are b-bbar pair backgrounds NPE from open HF meson
decays (B-mesons)?  Just curious.

You got it.
 

P5 Tabel I -- I assume momentum resolution effects are included in
the line shape entries.  Ref.1 is concerned about p-resolution and in
addition to the response, this table caption should note that p-resol.
is included in the line shape errors if that is true.

It is included and is now noted in the caption.
 

P5 L17-28 -- I did not find any discussion in the paper about the
use of max likelihood fitting. This turned out to be a big deal and
will be discussed in the response. This parag. would be the place
to say, briefly how the fits were done.

Good idea. The following was added: "The fit is permormed simultaneously to the like-sign and unlike-sign spectra using a maximum-likelihood method."
 

P6 L6 -- "miscalibration" sounds scary. Can this issue be explained
in the text, and more so in the responses, so that neither referee nor
the readers are put-off by the statement and dismiss the paper's results?

We now refer to it as a misalignment as well as quantifying the effect it had on the line shape.

P6 L26 -- I recommend against arguing with the referee over simple
wording changes that have equivalent meanings.  Is there a subtlety
here that I don't recognize?

We changed the wording and Manuel played diplomat. I never intended this to be the real response; it was more for the GPC. It's now fixed.

P6 Fig.3a -- The referee is asking that the legend "Upsilon -> e+e-"
say explicitly "Upsilon(1S+2S+3S) -> e+e-".  But also change to l+l-.
She/he wants the states listed explicitly.

Done.
 

P8 Fig 5c caption - same issue as above with the grey band. The
last sentence in the caption should read: "The grey band ... number
of binary collisions including resolution effects (see text)."

Done.
 

P9 L8 -- Referring to Fig. 6c, the 10-30% RAA is consistent with unity
also. This sentence should say, "..consistent with unity in peripheral
to more-central Au+Au collisions..."  BTW, "events" is jargon which we
all use, but I think it is better to say "collisions" here and throughout
the paper unless we are specifically discussing a triggered event in
DAQ.

Fair enough. I've updated the text to reflect that the RAA in 10-30% is consistent with unity as well.

Also, I changed event to collision where approriate in the text. Those changes are unhighlighted.


P10 L8 -- "With two possibilities.." implies that CNM and QGP are

the only possibilities for reducing yields.  There is at least the
possibility of modified fragmentation of HF quarks in a
dense system.  I recommend saying "Considering two possible
sources..."  which more accurately reflects what was done; we
considered these two effects and not others.

Good point! We fixed it. Thanks.

P10 L37-39 -- Isn't the "QGP only" preferred in Fig. 8b? Why
mention the other as "consistent" and not also mention the

one that fits best?

One thing to note here is that the "QGP only" model also includes the "no suppression" model in dAu. Seeing as no suppression is disfavored by the dAu study, we can argue that "QGP only" is not really favored. We made this more clear in the text.


Thorsten:

- p3, l31-l32: I don't like the formulation too much, maybe "...there exists a feed-down pattern in the bottomonium sector, and thus melting of the higher states affects also the measured yield of the lower states."

We've changed this section. See responses to Thomas' comments for further info.

- fig 1 take a lot of space for basically not much information, maybe a table would be sufficient?
Done

- p6, l6: TPC miscalibration sounds scary, maybe non-perfect TPC calibration?

We now refer to it as a misalignment as well as quantifying the effect it had on the line shape.

- p11, l5: I'm not too happy with the A^alpha discussion: after all it is a just a fit to the data. Have you used for this statement the alpha value from our own measurement, e.g. fig 4 bottom or the integrated one from fig 4 top? The integrated one is significantly above the midrapidity one, also for E772
Fair point. We discussed what we need to in the previous paragraph and we've removed this sentence.

Responses to PLB Referees

 Responses to Reviewers' comments:

We would like to thank the referees for the insightful and constructive comments. We discuss below our detailed replies to your questions and the corresponding explanation of changes to the manuscript. But before we go into the replies to the comments, we want to make the referees aware of changes to the results that were prompted via our studies of the systematic effects on the yield extraction.  Since this paper deals with cross sections and with nuclear-modification factors, both of which involve obtaining the yields of the Upsilon states, this change affects all the results in the paper. We therefore wanted to discuss this change first. Please note that the magnitude of these effects do not change the overall message of the paper.

We wanted to alert the referees up-front about this important change before we proceeded into the detailed responses.  This study was indirectly prompted by one of the questions from Referee 2 regarding systematic effects from yield extraction.

In the process of investigating the systematic difference between extracting the upsilon yield through simultaneous fitting compared to background subtraction as requested by the referee, we also studied the effects of chi^2 fits (specifically of Modified Least-Squares fits) compared to maximum-likelihood fits. We used chi^2 fits in our original submission. We were aware that extracting yields using a chi^2 fit introduces a bias (e.g see Glen Cowan's "Statistical Data Analysis", Sec. 7.4). The size of the bias is proportional to the value of the chi^2 of the fit.  In the case of the Modified Least-squares fit, when fitting a histogram including the total yield as a fit parameter, the yield will on average be lower than the true yield by an amount equal to chi^2.  The relative bias, i.e. the size of the bias divided by the extracted yield, goes to zero in the large yield limit, which is why for cases with large statistics this effect can be negligible.  We had attempted to mitigate the effects of this bias by using the integral of the data, since this removes the bias completely in the signal-only case.  But a bias remains in the case where there are both signal and background present. For our case, the yield extracted from the fit for the background is also biased toward lower values, and since we used this background estimate to subtract from the integral of the data in the extraction of the Upsilon yields, these biased the Upsilon yields towards higher values.   Through simulation studies, where we include signal and 3 background components as in our analysis, we were able to quantify these effects. Given that in some cases the biases could be of order 10-20%, the fits needed to be redone in order to remove the bias. The solution is straightforward since the extraction of yields using a maximum-likelihood fit is unbiased.  We have studied the difference of a modified-least squares fit and a maximum-likelihood fit and confirmed that the yield extraction in the latter method is essentially unbiased. We therefore have redone all the fits to extract the Upsilon yields via maximum-likelihood fits. The revised results are now quoted in the paper. The overall message of the paper is not affected by these changes.

We proceed next to answer the specific points raised by the reviewers.

Reviewer #1: This paper reports results on Y production in pp, dAu, and AuAu
collisions at top RHIC energy. It contains original and important
results and clearly qualifies for publication in PLB. However, there
are many aspects of the paper which need attention and/or improvement
prior to publication. They are detailed below:

1. the introduction is carelessly written. For example, the value
quoted for the pseudo-critical temperature near mu = 0 of 173 MeV is
taken from an old publication in 2003. Recent lattice results from the
Wuppertal-Budapest group (PoS LATTICE2013 (2013) 155) and the Hot QCD
Collaboration (Phys.Rev. D81 (2010) 054504) imply much lower T values
near 150 MeV and are far superior in terms of lattice sizes and spacing.

There are certainly newer results, which we now cite in the paper. However, we note that the
the results from the Hot QCD collaboration (Phys.Rev. D81 (2010) 054504) do not imply
much lower T values.  In that paper, in section IV "Deconfinement and Chiral aspects of the QCD transition", when discussing the deconfinement transition temperature range the authors write:
"...we have seen that the energy density shows a rapid rise in the temperature interval T = 170200. MeV. This is usually interpreted to be due to deconfinement, i.e., liberation of many new degrees of freedom". 
Therefore, this does not indicate T values near 150 MeV. In addition, they also mention this range when discussing their results for the renormalized Polyakov loop, which
is the parameter most closely related to the deconfiment transition, being that it is the exact order parameter in the pure
gauge case: 
"The renormalized Polyakov loop rises in the temperature interval T = 170200 MeV where we also see the rapid increase of the energy density."
Therefore, the results from the Hot QCD collaboration do not imply T values near 150 MeV.

In addition, in reference 9 of the Wuppertal-Budapest group (JHEP 1009 (2010) 073 arXv:1005.3508), which is a paper comparing the various results for Tc between the Wuppertal-Budapest and HotQCD groups, again the results for the renormalized Polyakov loop (figure 7, right) indicate a broad transition region in the region T=160-200 MeV.  They do have a table discussing values of Tc of about 147 MeV, but that is for the chiral transition, which is not the most relevant one for quarkonium suppression.   
When they look at the trace anomaly (e-3p)/T^4, they see 154 MeV for the Tc value.  They in addtion make the point that the transition is a broad crossover, which is something we also say in our paper.  The fact that the transition is a broad crossover leads to differences in the estimates of the pseudo-critical temperatures depending on which observable is used.  As an example, in the caption of Table 2, where they give the values of Tc for many observables, they mention that the Bielefeld-Brookhaven-Columbia-Riken Collaboration obtained Tc=192. They also note "It is more informative to look at the complete T dependence of observables, than
just at the definition-dependent characteristic poins of them." So given the above, we will modify the paper to give a range of temperatures, 150-190, and cite the papers from the
Wuppertal-Budapest and HotQCD collaborations.  

also the discussion on whether charmonium or bottomonium 'is a cleaner
probe..' does not get to any of the real issues, such as the complex
feeding pattern in the Y sector and the crucial question of whether Y
mesons reach equilibrium in the hot fireball as required to interpret
the apparent sequential melting pattern in terms of 'break-up'
temperatures. 
 

 
The issues we discuss, in our opinion, are real issues.  We discuss co-mover absorption and the interplay between suppression and statistical recombination of uncorrelated charm pairs. These have been a topic of intense interest in the charmonium case for over a decade.  We certainly agree that these are not the only issues, but in this paper we aim to present the result of our measurement, so we cannot give a detailed review of all issues. However, the aim was to point out that for the bottomonium case, the expected contributions to either suppression or enhancement from both of these mechanisms are much smaller, and hence studying Upsilons is cleaner. The reviewer brings up the importaint issue of feed-down that affects the bottomonium as it does the charmonium sector.  We have added a few sentences regarding feed-down.  Regarding bottomonium, the feed-down contributions to the Upsilon states are not measured at RHIC energies yet. It is therefore assumed in the models used by Strickland, Rapp, etc. that the fraction of directly-produced Upsilon(1S) is ~51%, as measured in pp collisions at high pT at Tevatron energy. The original paper motivating the quarkonium sequential suppression by Digal, Petreczky, and Satz discussed feed-down as part of the impetus for looking for suppression of the Upsilon(1S). Given the ~51% direct Upsilon fraction, an R_AA of the Upsilon(1S) as low as ~0.51 would not necessarily imply suppression of the direct 1S, but could be due solely to suppression of the excited states. We have added text about this point in the paper, in discussing the R_AA(1S) result.

The reviewer also mentions that there is a crucial question as to 
whether the Upsilon mesons reach equilibrium with the fireball as a requirement to interpret the sequential melting pattern. We respectfully disagree with the referee in this matter. The Upsilon is by definition not in equilibrium. The only requirement of course is that the medium is deconfined. In lattice QCD studies only the medium is thermalized; the potential between the heavy quarks is screened independent of whether the Upsilon is in equilibrium or not. We discussed this issue with lattice expert Peter Petreczky who confirmed our view.

 

furthermore, statistical recombination is not a 'complication' but a
direct measure of deconfinement. And the smallness of off-diagonal
terms in the recombination matrix does not imply absence of
recombination as the diagonal terms can be substantial.

We agree that statistical recombination is an indication of deconfinement, but from the experimental side, it has made the interpretation of the results more complicated, because one needs to take into account the interplay of suppression and recombination.  Because this effect is negligible for the bottomonium states even at LHC energies, the quantitative interpretation of the experimental results is less complicated. It is in this sense that the word "complication" is meant.
 

Also the newest results on p-Pb collisions from the LHC are entirely
ignored, see, e.g., arXiv:1308.6726.

We are aware of the quarkonium pPb results from LHC, however there is not a way to make a direct comparison to LHC results, because there are no pPb results on the nuclear modification factor of Upsilons.  The results from ALICE in the reference given above are for the J/psi meson, and they are also for the forward-backward kinematic range.  There are also results from CMS (arXiv:1312.6300) for Upsilon mesons at midrapidity, but these are in the form of ratios of the yield of the excited states to the ground states in a given system (pp, pPb, PbPb), and of double ratios, i.e. excited-to-ground-state ratios in pPb divided by excited-to-ground-state ratios in pp.  These give us relative suppression of the excited states, whereas our results are for absolute suppression, and are therefore not directly comparable. The only quantitative comparison to the CMS data we can make is to estimate a double ratio for the excited states. The double ratio we find is consistent with the result from pPb from CMS, but it is also consistent with 1, i.e. no suppression of the excited states relative to the ground state in pPb compared to pp (We find the double ratio = 0.72 +/- 0.37). We will make a comment about this in the paper, and cite the CMS pPb result.  But the advantage of the results we are presenting is that we have fully corrected nuclear modification factors, which convey more information than relative suppression. 
 

2. section on experimental methods

no detail is given concerning the crucial momentum resolution but it
is stated at the end of this section that cuts were adjusted for
different systems such that 'tracking and electron id would be the
same across the 3 data sets'. On the other hand, already in Fig. 1 we
see a strong dependence of the mass resolution on the system even for
low multiplicities as in pp and p-Pb. The effect must be much stronger
in Pb-Pb as is indeed visible in Fig. 4. Especially in view of the
importance of resolution for the separation of excited Y states this
referee has to be convinced that the systematic errors are under
control for momentum and pid measurements as a function of
multiplicity. Also how the systematic errors for the separation of Y'
and Y'' from Y are determined as a function of multiplicity needs to
be demonstrated explicitely.

We agree that the mass resolution is very important for the results of the paper, and need to be discussed.  We added text to discuss the Upsilon mass resolution, and how it was studied as a function of TPC multiplicity (we focus on mass resolution, but this is directly related to the momentum resolution of the electron tracks used to reconstruct the Upsilon).  We studied the mass resolution using both simulations and data-driven methods.  Regarding the momentum resolution and the difference of the mass width seen in the pp compared to the dAu and AuAu plots, the majority of the difference between the pp lineshape and the dAu/AuAu lineshapes comes from a miscalibration in the TPC which was corrected in the pp dataset via a reproduction of the raw data, but due to time constraints was not corrected in the dAu and AuAu datasets. With the distortion correction, the pp mass resolution is found to be 1.3%.  If there were no distortions in Au+Au, we find in peripheral events a mass resolution for the Upsilon(1S) of 1.7%, which widens to 2.0% for central events, based on simulations. In order to ensure that we had this resolution effect under quantitative control, in addition to studying it via embedding simulated tracks into real collision events, we also studied the difference in the reconstructed mass of every reconstructed di-electron pair between the corrected and uncorrected pp datasets on an event-by-event basis. We were able to determine the additional mass smearing introduced by this TPC distortion, and this data-driven knowledge was used in the determination of the line shapes in dAu and in Au+Au.  The additional smearing introduced by the TPC distortion resulted in a mass resolution for the Upsilon(1S) of 2.7%, widening to 2.9% for central events.  For d+Au, the mass resolution is also found to be 2.7%, consistent with the peripheral events in AuAu. Finally, given the importance of the resolution for the separation of the states, we also used one additional data-driven method to check the resolution. We used the data from Au+Au and performed a chi^2 scan varying the mass-width parameter of the Upsilon line shape to see if this would give the same results as those found from the pp event-by-event mass-smearing data-driven study.  The results were consistent with each other, giving us confidence that the mass resolution is under control.  We used the shape of the chi^2 vs. resolution-parameter derived from the data to assign an uncertainty to our mass-resolution parameter knowledge, and used this to estimate a systematic uncertainty on the yields.
We have added a few sentences to the text towards the end of the Experimental  Methods section to give the relevant mass resolution numbers, and to make it clear that the mass resolution is different for pp compared to both dAu and AuAu due to the TPC distortion.  We also added some sentences to discuss this in the description of the invariant mass figures.
The systematic uncertainties due to our knowledge of the line-shapes, which are directly related to the separation between the Upsilon(1S) and the excited states, are also listed in the systematic uncertainty table that we added to the paper. The rows listing the uncertainty due to the line shape, including these mass resolution effects and the uncertainty in the knowledge of these TPC distortions, are given in the table.  Finally, we also added a systematic uncertainty to the extraction of the Upsilon(1S) yield based on the purity of our mass cut.  This is affected not only by the knowledge of the line shapes, as discussed above, but also by the possible suppression of the excited states.  We estimated this uncertainty by comparing the case of no suppression to that of complete suppression of the excited states, and recalculated the Upsilon(1S) purity for each.  The systematic uncertainty table has a row giveing the value of this uncertainty on the Upsilon(1S) yield, and we also added text to clarify it in the paper.


3.  Fig. 2b  

even at y = 0 the difference between data and models is less than 2
sigma, taking uncertainties due to the pp reference into account and I
don't believe it makes sense to argue about effects beyond shadowing
and initial state parton energy loss in these data. 

With the new fit results, only the point at y=0 is different from the models, and while the difference is now of order ~3sigma, the two other points do not show any deviation from the models. The text has been changed removing the sentence mentioning effects beyond shadowing.  Also, thanks to this comment, we realized that we had plotted the full pp cross section systematic uncertainty on the figure, but for the purposes of R_dAu, some of these systematic uncertainties cancel.  Therefore, the band illustrating the systematics due to the pp reference should have been smaller, and this has now been corrected.
 

4. in Fig. 3 the size of the systematic errors should be indicated.

The problem is that none of the data points from E772 had systematic uncertainties, so we cannot include them.  We have indicated the size of our systematics in the plots. 
 

5.  in Fig. 5 it is demonstrated that the observed suppression near
midrapidity is independent of system size (N_part). This could imply
that the higher Y states are already disappeared in dAu
collisions. This is mentioned briefly in the conclusion, but could be
stressed more. 

The statement we made in the paper is complementary to the one suggested by the referee. We state at the end of the paper that we cannot claim that the suppression in AuAu is unambiguously from color deconfinement in AuAu given the suppression in dAu.  The reason we stated it like this is that the expectation was for only a minimal amount of suppression in dAu, but our results are a call for caution and for considering other hypotheses.  The referee's comment is a call to consider a specific hypothesis: that the higher Upsilon states already dissappear in dAu collisions. This is a hypothesis that is not accounted for yet in any model. While we are not advocating any particular hypothesis for dAu suppression, we can add a sentence phrased as suggested here, just to stress that our data elicit new thinking about Upsilon suppression in dAu.


6.  At LHC energy, the anisotropic model of Strickland reproduces well

the centrality dependence of R_AA but not the rapidity dependence,
see, e.g. the final session of the recent hard probes meeting in South
Africa.

The predictions from Strickland shown in Fig. 4 are rapidity-dependent. Our data agree fairly well in both rapidity ranges. The rapidity range examined by the slides shown in Strickland's Hard Probes talk (|y|<4.0) is much wider than the ranges we examine (|y|<1.0). Looking at the models, we do not expect to see much variation at all in the range we examine which is consistent with our observation. To see this variation, we would need to examine a much wider rapidity range which is not the focus of this paper.  (To constrain models at larger rapidities, it will be interesting to see the PHENIX results near |y|~2, which should be submitted for publication soon.)
 

7.  The presentation in Fig. 6 on the quantitative evaluation of
different model assumptions compared to data depends again strongly on
the size of the systematic errors, see the comment in section 2.

We've added a table and a new plot summarizing efficiencies and systematics.

 

----------------------------------------------------------------------------------------------------------------------------------------------------------------------

Reviewer #2: I have read the manuscript PLB-D-13-01645 submitted to me for review.
The authors present a detail analysis on the suppression of Y production in d+Au and Au+Au collisions at sqrt(s_NN)=200 GeV using the STAR detector at RHIC. The article is very well written and deserves publication. However, I would like to suggest considering the following remarks to improve the understandability of the article:

1. Page 1, column 1, paragraph 1: The now accepted value for the critical temperature (chiral transition) is Tc = 150 - 160 MeV (depending on the exact definition of the observables). Reference 3 is outdated and should be replaced by more recent publications, i.e. arXiv:1005.3508 [hep-lat]

See response to first reviewer's comment #1. References have been updated. Furthermore, the Tc noted here (the chiral transition) is not the relevant phase transition for quarkonium suppression. The more relevant one is the deconfinement transition (which is somewhat broad as currently noted in the text).


2. Page 2, column 2, paragraph 1: Please quantify the corrections due to the trigger bias w.r.t. the event centrality. Same for the tracking efficiency as a function of N_part. How does acceptance times efficiency for detecting Y as a function of rapidity and N_part looks like?

Added a new figure summarizing the total efficiency as a function of N_part and rapidity.


3. Page 3, column 1, paragraph 1: statement "some information will be lost" is too general! What are the systematic uncertainties arising from the different methods (same-event like-sign CB, fit to the CB) of the combinatorial background subtraction? What is the signal significance, in particular in the d+Au measurement? How does the signal looks like after CB and physical background subtraction? Systematic errors should be clearly mentioned.

Many thanks to the referee for mentioning this. In the process of investigating the systematic difference between extracting the upsilon yield through simultaneous fitting compared to background subtraction, we also investigated the effects of chi^2 fits compared to likelihood fits. We used chi^2 fits in our original submission. We were aware that extracting yields using a chi^2 fit introduces a bias. We attempted to minimize this bias by extracting the yields using the integral of the data. However, we still needed to subtract the backgrounds and the bakground yields came from the fits. Through investigation, we have demonstrated that chi^2 fits systematically underestimate the background yield, leading to an overestimate of the upsilon signals.

We have studied these effects through various MC simulations in order to extract the biases. The likelihood fits have negligible biases. Furthermore, and to get back to the original question posed by the referee, in these simulations we obtained the variance of our results when doing simultaneous fits when compared to background-subtracted fits. We found a reduction in the variance when using simultaneous fits which was our original impetus. We also found no systematic effect in the expectation values of the yields obtained by the two different fitting methods. However, given the reduction in the variance of the extracted yield (i.e. in their error) in the simultaneous fit, we favor this method since it introduces a smaller uncertainty. We have redone all of our fits using the likelihood method and we corrected for any extraction biases seen through simulation.

Regarding signal significance, in all cases we see significant signals in d+Au. This can be infered by examining Fig. 3a and comparing the size of the statistical+fit error bars to the measured value of the cross section. This ratio is a good indicator of the statistical significance of our signal. For example, the dAu signal at |y|<0.5 has a significance of 11.7/3.2 = 3.7 sigma.

Since the referee also asked about systematic uncertainties, we have added a full table covering all measured sources of systematic uncertainty and added additional comments about the main sources in the text. 

4. Fig 1: It would be easier for reader if the range of the y axis would be the same in Fig 1a and Fig 1b. Why is the explanation of the grey curves in the figure discussed in this complicated way, to my understanding the gray band simply shows the pp yield scaled by the number of binary collisions? If so, the label could read simply pp*<N_coll>.

The axes in Figs. 1a and 1b now match. We've relabeled the gray band.
 

5. Fig 1a: From where the line shape for pp comes from? It seems NOT to fit experimental data, i.e. all data points around 9 GeV/c^2 and below. Is it then evident to take as a cross section the integral of the data points?

The line shape in pp comes from simulations embedded in real data. Below 9 GeV, the lineshape threads between high and low datapoints. It cannot fit exactly to all of them without introducing wiggles in the function.
 

6. Page 3, column 2, paragraph 1: How was the measured Y(1S+2S+3S) yield transformed to cross section?

The cross section was calculated by correcting for EID efficiencies, triggering efficiencies, and acceptance to get a corrected yield. We then divided by the integrated luminosity to get a cross section.
 


7. Page 3, column 2, paragraph 3 (wording):  "Hence, averaging between forward and reverse rapidities is not warranted as it is in

p+p." -->  "Hence, averaging between forward and backward rapidities is not justified as it is in p+p." sounds more understandable.

Since the two words are very closely related (Merriam-Webster includes "justification" as one of the definitions of "warrant"), this is more a matter of style. The authors prefer the word "warranted."


8. Page 4: Try to arrange the placement of Figs such that there will not be a single line of the text within one column.

Done

9. Fig 2: also here Fig a and Fig b could be presented with the same range on the Y axis, e.g. from -3 to 3.

Done.


10. Fig 2a : what is shown here is Y(1S+2S+3S), moreover PHENIX results on Y -> mu+mu- are shown in the same plot, that is why the figure label should be changed, i.e. Y->e+e- should be replaced by Y(1S+2S+3S)

We changed the label to Y->l+l- to represent leptons.

11. Page 4, column 2, paragraph 2: <N_coll> (not <N_bin>) is commonly used as notation for the number of binary collisions. Sigma_AA is sigma^tot_AA (same for pp). It is important to indicate in the text the values for the total inelastic cross sections in pp, dA and AA and <N_coll> used to calculate R_AA.

Now using <N_coll>. Inelastic cross sections are provided inline.


 

12. Page 4, column 2, paragraph 3: In view of the discussion would it be helpful to also show R_AuAu vs. Rapidity?

We have addede new plots to the paper, and given the length considerations, and that this plot doesn't really add any new information beyond the existing tables and figures, for the sake of space, we would prefer to leave this plot out.


13. Page 6, column 1, paragraph 1: Which function has been used to fit the CB - exponential? Again, what are the systematic uncertainty arising from the different methods (same-event like-sign CB, fit to the CB) of the combinatorial background subtraction. See also comment 4. concerning the label.

The function used to model the CB is now discussed in the text. Systematics from the fit methods are summarized in Tab. I.

14. Page 6, column 1, paragraph 2: The statement "Similar suppression is found by CMS in PbPb collisions (37)" should be moved to the paragraph 4 where the authors discuss Y(1S) suppression. Actually, for the same value of N_part=325 R_AuAu=0.54+-0.09 as for R_PbPb=0.45

Done.

15. Page 6, column 1, paragraph 4: How did the authors derived: R_AA(1S+2S+3S) = R_AA(1S)*0.69?

We calculate this number by relating the two nuclear modification factors. For the (1S+2S+3S) case, this needs the ratio of the yields of (1S+2S+3S) in AA to the same yield in pp.  Since the R_AA(1S) is the ratio of the yield of the 1S state in AA to that in pp, one can take this out as a common factor in the R_AA(1S+2S+3S), obtaining the relation R_AA(1S+2S+3S)=R_AA(1S) * (1+ N_AA(2S+3S)/N_AA(1S))/(1+N_pp(2S+3S)/N_pp(1S)), where N_AA refers to the yield obtained in AA collisions and N_pp refers to the yield obtained in pp collisions.  This equation makes no assumptions.  When one takes the additional hypothesis that the yield in AA of the excited states is zero, the factor becomes 1/(1+N_pp(2S+3S)/N_pp(1S)). So with the ratio of excited states to ground state in pp collisions, one can find the multiplicative factor.  We calculated this ratio in two manners: first, by using the PDG branching ratios together with NLO pQCD calculations for the upsilon production cross sections (from Ref 21 by Frawley, Ullrich, and Vogt), and, second, by using the measured 2S/1S and 3S/1S ratios. For example, these ratios have been measured at sqrt{s}=38.8 GeV and also at sqrt(s)=2.76 TeV from CMS, and are relatively independent of sqrt(s), or even whether the collision system is pp or pA. In the first case where we used the pQCD cross section and PDF branching ratios, we get 0.69 for the multiplicative factor. In the second case where we only used measured ratios, we get 0.72 +/- 0.02.  The difference between using the low-sqrt(s)-pA data or the CMS pp data at 2.76 TeV is 0.01, which is smaller than the statistical error of the CMS data.
We had aimed to keep the text brief, since we were mindful of the space constraints, but given this question, we have added a few more sentences and references to clarify the R_AA(1S+2S+3S)=R_AA(1S)*0.7 statement, and also reduced our significant figures, quoting only a factor of 0.7.
 

16. Page 6, column 2, paragraph 2: What are the uncertainties on Drell-Yan and bbbar cross sections and how does it influence the significance of the signal.

Various normalizations are used in the fit. This is accounted for in the correllation

17. http://arxiv.org/pdf/1109.3891.pdf reports on the first measurement of the Y nuclear modification factor with STAR. It is probably worth to mention this work in the ms.

We are certainly aware of the proceeding mentioned here, which showed preliminary results for these analyses. The author of the proceedings was a member of the institute where the primary analsys shown in this paper was done. The reason we omit the citation to this and to other proceedings where the preliminary results have been shown is that it is a policy of the STAR collaboration to not cite our own proceedings showing preliminary data. This is partly with the goal to make it clear that the final results presented in a given paper, which have gone through the full collaboration review and through the external peer-review process, are the ones that should be referenced once they are available.


18. The R_AA of J/psi (p_T > 5 GeV), Y(1S) and an upper limit on the R_AA (2S+3S) was obtained in STAR. I would like to suggest to add a plot showing R_AA as a function of binding energy as a summary figure (also as a key figure to the long discussion on the extraction of the upper limit on R_AA(2S+3S)).

Good idea. We added this figure towards the end of the paper.


In summary, this ms. contains very interesting results and I propose publication in Phys. Letter B after the authors have taken care of the remarks above.

We thank the referee for her/his comments and remarks, which have helped improve the paper.  We hope that we have addressed the issues raised, and adequately answered the questions posed, and look forward to the publication of the paper.


Upsilon pp, dAu, AuAu GPC E-mail Responses

 This is a page to house long e-mail responses.

Using Pythia 8 to get b-bbar -> e+e-

We used Pythia 8 to produce b-bbar events. First we used the default Pythia 8. Macro for running with default parameters is here. We then used the STAR Heavy Flavor tune v1.1 for Pythia 8.  The macro for running with the STAR HF tune is here.

The cross-sections reported by Pythia (numbers after 5M events) using the default parameters:

  *-------  PYTHIA Event and Cross Section Statistics  -------------------------------------------------------------*
 |                                                                                                                 |
 | Subprocess                                    Code |            Number of events       |      sigma +- delta    |
 |                                                    |       Tried   Selected   Accepted |     (estimated) (mb)   |
 |                                                    |                                   |                        |
 |-----------------------------------------------------------------------------------------------------------------|
 |                                                    |                                   |                        |
 | g g -> b bbar                                  123 |    19262606    4198826    4198275 |   6.971e-04  1.854e-07 |
 | q qbar -> b bbar                               124 |     3126270     801174     800981 |   1.331e-04  8.216e-08 |
 |                                                    |                                   |                        |
 | sum                                                |    22388876    5000000    4999256 |   8.303e-04  2.028e-07 |
 |                                                                                                                 |
 *-------  End PYTHIA Event and Cross Section Statistics ----------------------------------------------------------*

So gg initiated subprocess has a 0.697 ub cross section and the q-qbar initiated subprocess has a 0.133 ub cross section. The sum for both subprocesses pp -> b bbar is 0.830 ub. 

Using the STAR HF Tune, the cross section statistics reported by Pythia change to the following:

 *-------  PYTHIA Event and Cross Section Statistics  -------------------------------------------------------------*
 |                                                                                                                 |
 | Subprocess                                    Code |            Number of events       |      sigma +- delta    |
 |                                                    |       Tried   Selected   Accepted |     (estimated) (mb)   |
 |                                                    |                                   |                        |
 |-----------------------------------------------------------------------------------------------------------------|
 |                                                    |                                   |                        |
 | g g -> b bbar                                  123 |    31956918    4520459    4520459 |   9.247e-04  2.542e-07 |
 | q qbar -> b bbar                               124 |     2259563     479541     479541 |   9.817e-05  8.544e-08 |
 |                                                    |                                   |                        |
 | sum                                                |    34216481    5000000    5000000 |   1.023e-03  2.682e-07 |
 |                                                                                                                 |
 *-------  End PYTHIA Event and Cross Section Statistics ----------------------------------------------------------*

 

The cross section increases to 1.023 ub with the STAR HF Tune v1.1.  The main changes to the default parameters are the reduction of the bottom quark mass from 4.8 (default) to 4.3 GeV/c2, the change of PDF from CTEQ5L (default) to the LHAPDF set MRSTMCal.LHgrid, and the choice of renormalization and factorization scales.

The selection of e+e- in the final state is done by following the fragmentation of the b or bbar quark into a B meson or baryon, and then looking at its decay products to find an electron or positron.  The pT distribution of the genrated b quarks is shown below.

Fig. 1: Generated b quarks.

 

The <pT> of the b quarks is 3.3 GeV.  These then fragment into B mesons and baryons.  As an example, we plot here the B0 and B0-bar pT distribution, below.

Fig. 2:Pt distribution of B0 and B0-bar mesons.

The <pT> of the B mesons is 3.055 GeV/c, one can estimate the peak of the Z distribution (most of the momentum of the b quark is carried by the meson, so it should be close to 1) as 3.055/3.331=0.92.

After the beauty hadrons are produced, they can decay producing electrons and positrons.  We search for the e+e- daughters of the beauty hadrons, their pT distribution is shown below.

Fig. 3: pT distribution of the e+ e- daughters of the b quarks.

When an event has both an electron and positron from the b-bbar pair this can generate a trigger.  However, these are generated in all of phase space, and we mainly have acceptance at mid-rapidity.  The full rapidity distribution of the e+e- pairs is shown below:

Fig. 4: Rapidity distribution of the e+e- pairs from b decay.

The distribution is well approximated by a Gaussian with mean ~ 0 and width close to 1 (off by 4.3%).

We calculate the invariant mass. This is shown below:

Fig 6. Invariant mass spectrum of e-e+ pairs originating from b-bbar pairs.

The red histogram is for all e+e- pairs generated by Pythia.  The blue histogram is for pairs with |y_pair|<0.5, which is the region of interest. The distributions are fit to a function to parameterize the shape, shown in the black lines.  This is inspired by using a QCD tree-level power-law distribution multiplied with a phase-space factor in the numerator. The fit parameters for the blue line are:

  • b = 1.59 +/- 0.06
  • c = 27.6 +/- 5.8
  • m0 = 29.7 +/- 7.8

Using the STAR HF Tune, the parameters are:

  • b = 1.45 +/- 0.05
  • c = 64.2 +/- 26.1
  • m0 = 49.7 +/- 18.0

With the default parameters, in mass region 8 < m < 11 GeV/c2 and for |y|<0.5 the Pythia prediction is for a cross section of 29.5 pb.

With the STAR HF Tune, in the same phase space region the Pythia prediciton is for a cross section of 46.9 pb.

One can calculate from the Pythia cross section, the STAR efficiency*acceptance and the integrated luminosity the expected yield in the region 8< m < 11 GeV/c2. This gives 12 expected counts for trigger 137603, assuming the trigger doesn't affect the invariant mass shape.

However, tince the trigger has a turn-on region, we need to take this into account.  The turn on can be obtained by looking at the background counts in the real data.  By modeling the background with an error function of the form (erf((m-m0)/sigma)+1)/2 and multiplying by an exponential, we obtain the parameters m0=8.07 +/- 0.74 GeV/c2 and sigma = 1.75 +/- 0.45 GeV/c2. The fit to obtain the error function is shown below (it is one of the figures in the paper):

Fig. 7 Unlike-sign and like-sign invariant mass distributions from data. The like-sign is fit with and exponential multiplied by an erf.

We then need to apply this function to parameterize the turn-on region of the trigger to the b-bbar e+e- invariant mass spectrum.  We have one additional piece of information from the efficiency estimation: the overall acceptance * trigger efficiency * tracking efficiency and including additional PID cuts for the Upsilon(12) is 5.4%, we can use this to normalize the function after including the trigger turn-on so that at M=10 GeV/c2 it gives 5.4% of the yield before applying the trigger turn-on.  This way we take care of the trigger turn-on shape and the overall normalization given by the acceptance, efficiency, etc. obtained from the upsilon embedding.  This assumes that an e+e- pair with invariant mass identical to the upsilon will have identical efficiency and acceptance.  Using this, we estimate the yield in the region 8<m<11 including the trigger turn-on and acceptance and efficiency to be 19 counts from b-bbar in the Upsilon mass region in the entire dataset.

For the STAR HF Tune, the cross section is larger and the expected counts are larger:

 

 

Code to run Pythia and produce b-bbar -> e+ e- events

// main00.cc
// Modified from the main01.cc
// which is a part of the PYTHIA event generator.
// Copyright (C) 2008 Torbjorn Sjostrand.
// PYTHIA is licenced under the GNU GPL version 2, see COPYING for details.
// Please respect the MCnet Guidelines, see GUIDELINES for details.

// This is a simple test program.

#include "Pythia.h"

#include "TROOT.h"
#include "TFile.h"
#include "TH1.h"

bool isBHadron(int id) {
  // This snippet is meant to capture all B hadrons
  // as given in the PDG.
  if (id<0) id*=-1;
  if (id<500) return false;
  return (fmod(id/100,5.)==0.0 || id/1000==5);
}

using namespace Pythia8;
int main() {
  // Initialize root
  TROOT root("Manuel's ROOT Session","PYTHIA Histograms");

  // Generator. Process selection. LHC initialization. Histogram.
  Pythia pythia;
 
  // Uncomment line below to turns on all HardQCD processses
  // These are 111-116 and  121-124
  //pythia.readString("HardQCD:all = on");
 
  // Turn on only bbar production:
  // g g    -> b bbar (subprocess 123)
  // q qbar -> b bbar (subprocess 124)
  pythia.readString("HardQCD:gg2bbbar = on");
  pythia.readString("HardQCD:qqbar2bbbar = on");
 
  pythia.readString("PhaseSpace:pTHatMin = 20.");
 
  // Random number Generator Should be Set Here if needed (before pythia.init())
  // On seeds:
  // seed = -1 : default (any number < 0 will revert to the default).  seed = 19780503
  // seed = 0 : calls Stdlib time(0) to provide a seed based on the unix time
  // seed = 1 through 900 000 000: various numbers that can be used as seeds
 
  //pythia.readString("Random.setSeed = on");// doesn't work needs fixing
  //pythia.readString("Random.seed = 3000000");
 
  pythia.init( 2212, 2212, 200.);
  Hist mult("charged multiplicity", 100, -0.5, 799.5);
 
  TH1D* multHist = new TH1D("multHist","Multiplicity",100,-0.5,99.5);
  TH1D* bquarkPt = new TH1D("bquarkPt","bquarkPt",100,0,50);
  TH1D* bbarquarkPt = new TH1D("bbarquarkPt","bbar quark Pt",100,0,50);
  TH1D* B0mesonPt = new TH1D("BOmesonPt","B0mesonPt",100,0,50);
  TH1D* B0barmesonPt = new TH1D("BObarmesonPt","B0bar meson Pt",100,0,50);
  TH1D* electronFrombPt = new TH1D("electronFrombPt","electrons from b",100,0,30);
  TH1D* positronFrombPt = new TH1D("positronFrombPt","positrons from b",100,0,30);
  TH1D* epluseminusMinv = new TH1D("epluseminusMinv","e+ e- Inv. Mass",100,0,30);

  // Begin event loop. Generate event. Skip if error. List first one.
  for (int iEvent = 0; iEvent < 10000; ++iEvent) {
    if (!pythia.next()) continue;
    if (iEvent < 1) {pythia.info.list(); pythia.event.list();}
    // Find number of all final charged particles and fill histogram.
    // Find the b (id = 5) and bbar (id = -5), find their daughters,
    // if daughters include electron (id = 11) and positron (id=-11), calculate their
    // invariant mass
    // Status flags:
    //   21 incoming particles of hardest subprocess
    //   23 outgoing particles of hardest subprocess
    //   81-89 primary hadrons produced by hadronization process (B mesons, e.g.)
    //   91-99 particles produced in decay process or by B-E effects (e.g. the electrons)

    int nCharged = 0;
    int indexBQuark(0), indexBbarQuark(0);
    for (int i = 0; i < pythia.event.size(); ++i) {
      if (pythia.event[i].isFinal() && pythia.event[i].isCharged()) {
        ++nCharged;
      }
      Particle& theParticle = pythia.event[i];
    
      if (theParticle.id() == 5 ) {
    indexBQuark = i;
    //cout << "Mother 1, Mother 2 = " << theParticle.mother1() << ", " << theParticle.mother2() << endl;
      }
      if (theParticle.id() == -5) {
    indexBbarQuark = i;
    //cout << "Mother 1, Mother 2 = " << theParticle.mother1() << ", " << theParticle.mother2() << endl;
      }
    } // particle loop

    cout << "Found b quark at index " << indexBQuark << endl;
    cout << "Found bbar quark at index " << indexBbarQuark << endl;
    bquarkPt->Fill(pythia.event[indexBQuark].pT());
    bbarquarkPt->Fill(pythia.event[indexBbarQuark].pT());
    mult.fill( nCharged );
    multHist->Fill(nCharged);
    //cout << "Event " << iEvent << ", Nch= " << nCharged << endl;
    
    
    //Find hadronization products of b and bbar.
    int bQuarkDaughter1 = pythia.event[indexBQuark].daughter1();
    int bQuarkDaughter2 = pythia.event[indexBQuark].daughter2();
    int bbarQuarkDaughter1 = pythia.event[indexBbarQuark].daughter1();
    int bbarQuarkDaughter2 = pythia.event[indexBbarQuark].daughter2();
    
    // Obtain the two hadrons from the fragmentation process
    // Use the PDG id's for this.  All B mesons id's are of the form xx5xx, and
    // all B baryons are of the form 5xxx.
    // So we obtain the id, (make it positive if needed) and then test
    // to see if it is a meson with fmod(currId/100,5)==0.0
    // to see if it is a baryon with currId/1000==5
    int HadronFromBQuark(0), HadronFromBbarQuark(0);
    if (bQuarkDaughter1<bQuarkDaughter2) {
      cout << "Daughters of b Quark" << endl;
      for (int j=bQuarkDaughter1; j<=bQuarkDaughter2; ++j) {
    if (isBHadron(pythia.event[j].id())) {
      cout << "Fragmentation: b -> " << pythia.event[j].name() << endl;
      cout << "                 id " << pythia.event[j].id() << " at index " << j << endl;
      HadronFromBQuark = j;
    }
      }
    }
    if (bbarQuarkDaughter1<bbarQuarkDaughter2) {
      cout << "Daughters of bbar Quark" << endl;
      for (int k=bbarQuarkDaughter1; k<=bbarQuarkDaughter2; ++k) {
    if (isBHadron(pythia.event[k].id())) {
      cout << "Fragmentation : bbar -> " << pythia.event[k].name()  << endl;
      cout << "                     id " << pythia.event[k].id() << " at index " << k << endl;
      HadronFromBbarQuark = k;
    }
      }
    }
    // Search the daughters of the hadrons until electrons and positrons are found
    // if there are any from a semileptonic decay of a beauty hadron
    // Start with the b quark
    int Daughter(HadronFromBQuark), electronIndex(0), positronIndex(0);
    while (Daughter!=0) {
      cout << "Checking " << pythia.event[Daughter].name() << " for e+/e- daughters" << endl;
      if (pythia.event[Daughter].id()==-511) {
    // This is a Bbar0, enter its pT
    cout << "Filling Bbar0 pT" << endl;
    B0barmesonPt->Fill(pythia.event[Daughter].pT());
      }
      if (pythia.event[Daughter].id()==511) {
    // This is a B0, enter its pT
    cout << "Filling Bbar0 pT" << endl;
    B0mesonPt->Fill(pythia.event[Daughter].pT());
      }
      int nextDaughter1 = pythia.event[Daughter].daughter1();
      int nextDaughter2 = pythia.event[Daughter].daughter2();
      // search for electron or positron
      for (int iDaughter = nextDaughter1; iDaughter<=nextDaughter2; ++iDaughter) {
    if (pythia.event[iDaughter].id()==11) {
      cout << "Found electron" << endl;
      cout << pythia.event[iDaughter].name() << endl;
      electronIndex=iDaughter;
      electronFrombPt->Fill(pythia.event[electronIndex].pT());
      break;
    }
    if (pythia.event[iDaughter].id()==-11) {
      cout << "Found positron" << endl;
      cout << pythia.event[iDaughter].name() << endl;
      positronIndex=iDaughter;
      positronFrombPt->Fill(pythia.event[positronIndex].pT());
      break;
    }
      }// loop over daughters to check for e+e-
      
      // If we get here, that means there were no electrons nor positrons.
      // Set the Daughter index to zero now.
      Daughter = 0;
      // If any of the daughters is still a beauty-hadron, we can try again
      // and reset the Daughter index, but only if one of the daughters contains a
      // b quark.
      for (int jDaughter = nextDaughter1; jDaughter<=nextDaughter2; ++jDaughter) {
    if (isBHadron(pythia.event[jDaughter].id())) {
      //One of the daughters is a beauty hadron.
      Daughter = jDaughter;
    }
      }// loop over daughters to check for another b hadron
    }// end of search for electrons in all the daughters of the b quark
    
    // Now search among the daughters of the bbar quark
    Daughter=HadronFromBbarQuark;
    while (Daughter!=0) {
      cout << "Checking " << pythia.event[Daughter].name() << " for e+/e- daughters" << endl;
      if (pythia.event[Daughter].id()==-511) {
    // This is a Bbar0, enter its pT
    cout << "Filling Bbar0 pT" << endl;
    B0barmesonPt->Fill(pythia.event[Daughter].pT());
      }
      if (pythia.event[Daughter].id()==511) {
    // This is a B0, enter its pT
    cout << "Filling B0 pT" << endl;
    B0mesonPt->Fill(pythia.event[Daughter].pT());
      }
      int nextDaughter1 = pythia.event[Daughter].daughter1();
      int nextDaughter2 = pythia.event[Daughter].daughter2();
      // search for electron or positron
      for (int iDaughter = nextDaughter1; iDaughter<=nextDaughter2; ++iDaughter) {
    //cout << "daughter is a " << pythia.event[iDaughter].name() << endl;
    if (pythia.event[iDaughter].id()==11) {
      cout << "Found electron" << endl;
      cout << pythia.event[iDaughter].name() << endl;
      electronIndex=iDaughter;
      electronFrombPt->Fill(pythia.event[electronIndex].pT());
      break;
    }
    if (pythia.event[iDaughter].id()==-11) {
      cout << "Found positron" << endl;
      cout << pythia.event[iDaughter].name() << endl;
      positronIndex=iDaughter;
      positronFrombPt->Fill(pythia.event[positronIndex].pT());
      break;
    }
      }// loop over daughters to check for e+e-
      
      // If we get here, that means there were no electrons nor positrons.
      // Set the Daughter index to zero now.
      Daughter = 0;
      // If any of the daughters is still a beauty-hadron, we can try again
      // and reset the Daughter index, but only if one of the daughters contains a
      // b quark.
      for (int jDaughter = nextDaughter1; jDaughter<=nextDaughter2; ++jDaughter) {
    if (isBHadron(pythia.event[jDaughter].id())) {
      //One of the daughters is a beauty hadron.
      Daughter = jDaughter;
    }
      }// loop over daughters to check for another b hadron
    }//end of search for electron among daughters of bbar quark
    
    if (electronIndex!=0 && positronIndex!=0) {
      cout << "Found an e+e- pair from bbar" << endl;
      cout << "Ele 4-mom = " << pythia.event[electronIndex].p() << endl;
      cout << "Pos 4-mom = " << pythia.event[positronIndex].p() << endl;
      Vec4 epluseminus(pythia.event[electronIndex].p()+pythia.event[positronIndex].p());
      epluseminusMinv->Fill(epluseminus.mCalc());
    }
    else {
      cout << "No e+e- pair in event" << endl;
    }
    
  // End of event loop. Statistics. Histogram. Done.
  }// event loop
  pythia.statistics();
  //cout << mult << endl;

  //Write Output ROOT hisotgram into ROOT file
  TFile* outFile = new TFile("pythiaOutputHistos1M.root","RECREATE");
  multHist->Write();
  bquarkPt->Write();
  bbarquarkPt->Write();
  B0mesonPt->Write();
  B0barmesonPt->Write();
  electronFrombPt->Write();
  positronFrombPt->Write();
  epluseminusMinv->Write();
  outFile->Close();

  return 0;
}

 

Code to run with STAR HF Tune

// main00.cc
// Modified from the main01.cc
// which is a part of the PYTHIA event generator.
// Copyright (C) 2008 Torbjorn Sjostrand.
// PYTHIA is licenced under the GNU GPL version 2, see COPYING for details.
// Please respect the MCnet Guidelines, see GUIDELINES for details.

// This is a simple test program.

#include "Pythia.h"
#include "Basics.h"

#include "TROOT.h"
#include "TFile.h"
#include "TH1.h"

bool isBHadron(int id) {
  // This snippet is meant to capture all B hadrons
  // as given in the PDG.
  if (id<0) id*=-1;
  if (id<500) return false;
  return (fmod(id/100,5.)==0.0 || id/1000==5);
}

using namespace Pythia8;

double myRapidity(Vec4& p) {
  return 0.5*log(p.pPlus()/p.pMinus());
}

int main() {
  // Initialize root
  TROOT root("Manuel's ROOT Session","PYTHIA Histograms");

  // Generator. Process selection. LHC initialization. Histogram.
  Pythia pythia;
 
  // Shorthand for some public members of pythia (also static ones).
  //Event& event = pythia.event;
  ParticleDataTable& pdt = pythia.particleData;
  // The cmnd file below contains
  // the Pythia Tune parameters
  // the processes that are turned on
  // and the PDFs used
  // for the pythia run.
 
  pythia.readFile("main00.cmnd");
  UserHooks *oniumUserHook = new SuppressSmallPT();
  pythia.setUserHooksPtr(oniumUserHook);

  cout << "Mass of b quark " << ParticleDataTable::mass(5) << endl;
  cout << "Mass of b bar   " << ParticleDataTable::mass(-5) << endl;
 
  // Extract settings to be used in the main program.
  int    nEvent  = pythia.mode("Main:numberOfEvents");
  int    nList   = pythia.mode("Main:numberToList");
  int    nShow   = pythia.mode("Main:timesToShow");
  int nAllowErr  = pythia.mode("Main:timesAllowErrors");
  bool   showCS  = pythia.flag("Main:showChangedSettings");
  bool showSett  = pythia.flag("Main:showAllSettings");
  bool showStat  = pythia.flag("Main:showAllStatistics");
  bool   showCPD = pythia.flag("Main:showChangedParticleData");
 

  pythia.init();
  if (showSett) pythia.settings.listAll();
  if (showCS) pythia.settings.listChanged();
  if (showCPD) pdt.listChanged();

  Hist mult("charged multiplicity", 100, -0.5, 799.5);
 
  TH1D* multHist = new TH1D("multHist","Multiplicity",100,-0.5,99.5);
  TH1D* bquarkPt = new TH1D("bquarkPt","bquarkPt",100,0,50);
  TH1D* bbarquarkPt = new TH1D("bbarquarkPt","bbar quark Pt",100,0,50);
  TH1D* B0mesonPt = new TH1D("BOmesonPt","B0mesonPt",100,0,50);
  TH1D* B0barmesonPt = new TH1D("BObarmesonPt","B0bar meson Pt",100,0,50);
  TH1D* BplusmesonPt = new TH1D("BplusmesonPt","BplusmesonPt",100,0,50);
  TH1D* BminusmesonPt = new TH1D("BminusmesonPt","Bminus meson Pt",100,0,50);
  TH1D* BplusmesonPtCDFrap = new TH1D("BplusmesonPtCDFrap","BplusmesonPt |y|<1",100,0,50);
  TH1D* BminusmesonPtCDFrap = new TH1D("BminusmesonPtCDFrap","Bminus meson Pt |y|<1",100,0,50);
  TH1D* electronFrombPt = new TH1D("electronFrombPt","electrons from b",100,0,30);
  TH1D* positronFrombPt = new TH1D("positronFrombPt","positrons from b",100,0,30);
  TH1D* epluseminusMinv = new TH1D("epluseminusMinv","e+ e- Inv. Mass",300,0,30);
  TH1D* epluseminusRapidity = new TH1D("epluseminusRapidity","e+ e- y",80,-4,4);
  TH1D* epluseminusMinvMidRap = new TH1D("epluseminusMinvMidRap","e+ e- Inv. Mass |y|<0.5",300,0,30);

  // Begin event loop. Generate event. Skip if error. List first one.
  int nPace = max(1,nEvent/nShow);
  int nErrors(0);
  for (int iEvent = 0; iEvent < nEvent; ++iEvent) {
    if (!pythia.next()) {
      ++nErrors;
      if (nErrors>=nAllowErr) {
    cout << "Reached error limit : " << nErrors << endl;
    cout << "Bailing out! " << endl;
    break;
      }
      continue;
    }
    if (iEvent%nPace == 0) cout << " Now begin event " << iEvent << endl;
    if (iEvent < nList) {pythia.info.list(); pythia.event.list();}
    // Find number of all final charged particles and fill histogram.
    // Find the b (id = 5) and bbar (id = -5), find their daughters,
    // if daughters include electron (id = 11) and positron (id=-11), calculate their
    // invariant mass
    // Status flags:
    //   21 incoming particles of hardest subprocess
    //   23 outgoing particles of hardest subprocess
    //   81-89 primary hadrons produced by hadronization process (B mesons, e.g.)
    //   91-99 particles produced in decay process or by B-E effects (e.g. the electrons)

    int nCharged = 0;
    int indexBQuark(0), indexBbarQuark(0);
    for (int i = 0; i < pythia.event.size(); ++i) {
      if (pythia.event[i].isFinal() && pythia.event[i].isCharged()) {
        ++nCharged;
      }
      Particle& theParticle = pythia.event[i];
   
      if (theParticle.id() == 5 ) {
    indexBQuark = i;
    //cout << "Mother 1, Mother 2 = " << theParticle.mother1() << ", " << theParticle.mother2() << endl;
      }
      if (theParticle.id() == -5) {
    indexBbarQuark = i;
    //cout << "Mother 1, Mother 2 = " << theParticle.mother1() << ", " << theParticle.mother2() << endl;
      }
    } // particle loop

    cout << "Found b quark at index " << indexBQuark << endl;
    cout << "Found bbar quark at index " << indexBbarQuark << endl;
    bquarkPt->Fill(pythia.event[indexBQuark].pT());
    bbarquarkPt->Fill(pythia.event[indexBbarQuark].pT());
    mult.fill( nCharged );
    multHist->Fill(nCharged);
    //cout << "Event " << iEvent << ", Nch= " << nCharged << endl;
   
   
    //Find hadronization products of b and bbar.
    int bQuarkDaughter1 = pythia.event[indexBQuark].daughter1();//first daughter index
    int bQuarkDaughter2 = pythia.event[indexBQuark].daughter2();//last daughter index
    int bbarQuarkDaughter1 = pythia.event[indexBbarQuark].daughter1();
    int bbarQuarkDaughter2 = pythia.event[indexBbarQuark].daughter2();
   
    // Obtain the two hadrons from the fragmentation process
    // Use the PDG id's for this.  All B mesons id's are of the form xx5xx, and
    // all B baryons are of the form 5xxx.
    // So we obtain the id, (make it positive if needed) and then test
    // to see if it is a meson with fmod(currId/100,5)==0.0
    // to see if it is a baryon with currId/1000==5
    int HadronFromBQuark(0), HadronFromBbarQuark(0);
    if (bQuarkDaughter1<bQuarkDaughter2) {
      cout << "Daughters of b Quark" << endl;
      for (int j=bQuarkDaughter1; j<=bQuarkDaughter2; ++j) {
    if (isBHadron(pythia.event[j].id())) {
      cout << "Fragmentation: b -> " << pythia.event[j].name() << endl;
      cout << "                 id " << pythia.event[j].id() << " at index " << j << endl;
      HadronFromBQuark = j;
    }
      }
    }
    if (bbarQuarkDaughter1<bbarQuarkDaughter2) {
      cout << "Daughters of bbar Quark" << endl;
      for (int k=bbarQuarkDaughter1; k<=bbarQuarkDaughter2; ++k) {
    if (isBHadron(pythia.event[k].id())) {
      cout << "Fragmentation : bbar -> " << pythia.event[k].name()  << endl;
      cout << "                     id " << pythia.event[k].id() << " at index " << k << endl;
      HadronFromBbarQuark = k;
    }
      }
    }
    // Search the daughters of the hadrons until electrons and positrons are found
    // if there are any from a semileptonic decay of a beauty hadron
    // Start with the b quark, the b-bar quark loop comes after this
    int Daughter(HadronFromBQuark), electronIndex(0), positronIndex(0);
    while (Daughter!=0) {
      cout << "Checking " << pythia.event[Daughter].name() << " for e+/e- daughters" << endl;
      if (pythia.event[Daughter].id()==-511) {
    // This is a Bbar0, enter its pT
    cout << "Filling Bbar0 pT" << endl;
    B0barmesonPt->Fill(pythia.event[Daughter].pT());
      }
      if (pythia.event[Daughter].id()==511) {
    // This is a B0, enter its pT
    cout << "Filling Bbar0 pT" << endl;
    B0mesonPt->Fill(pythia.event[Daughter].pT());
      }
      Vec4 daughterVec4 = pythia.event[Daughter].p();
      double daughterRap = myRapidity(daughterVec4);

       if (pythia.event[Daughter].id()==-521) {
    // This is a Bminus, enter its pT
    cout << "Filling Bminus pT" << endl;
    BminusmesonPt->Fill(pythia.event[Daughter].pT());
    if (fabs(daughterRap)<1.0) {
      BminusmesonPtCDFrap->Fill(pythia.event[Daughter].pT());
    }
      }
      if (pythia.event[Daughter].id()==521) {
    // This is a Bplus, enter its pT
    cout << "Filling Bplus pT" << endl;
    BplusmesonPt->Fill(pythia.event[Daughter].pT());
    if (fabs(daughterRap)<1.0) {
      BplusmesonPtCDFrap->Fill(pythia.event[Daughter].pT());
    }
      }
     int nextDaughter1 = pythia.event[Daughter].daughter1();
      int nextDaughter2 = pythia.event[Daughter].daughter2();
      // search for electron or positron
      for (int iDaughter = nextDaughter1; iDaughter<=nextDaughter2; ++iDaughter) {
    if (pythia.event[iDaughter].id()==11) {
      cout << "Found electron" << endl;
      cout << pythia.event[iDaughter].name() << endl;
      electronIndex=iDaughter;
      electronFrombPt->Fill(pythia.event[electronIndex].pT());
      break;
    }
    if (pythia.event[iDaughter].id()==-11) {
      cout << "Found positron" << endl;
      cout << pythia.event[iDaughter].name() << endl;
      positronIndex=iDaughter;
      positronFrombPt->Fill(pythia.event[positronIndex].pT());
      break;
    }
      }// loop over daughters to check for e+e-
     
      // If we get here, that means there were no electrons nor positrons.
      // Set the Daughter index to zero now.
      Daughter = 0;
      // If any of the daughters is still a beauty-hadron, we can try again
      // and reset the Daughter index, but only if one of the daughters contains a
      // b quark.
      for (int jDaughter = nextDaughter1; jDaughter<=nextDaughter2; ++jDaughter) {
    if (isBHadron(pythia.event[jDaughter].id())) {
      //One of the daughters is a beauty hadron.
      Daughter = jDaughter;
    }
      }// loop over daughters to check for another b hadron
    }// end of search for electrons in all the daughters of the b quark
   
    // Now search among the daughters of the bbar quark
    Daughter=HadronFromBbarQuark;
    while (Daughter!=0) {
      cout << "Checking " << pythia.event[Daughter].name() << " for e+/e- daughters" << endl;
      if (pythia.event[Daughter].id()==-511) {
    // This is a Bbar0, enter its pT
    cout << "Filling Bbar0 pT" << endl;
    B0barmesonPt->Fill(pythia.event[Daughter].pT());
      }
      if (pythia.event[Daughter].id()==511) {
    // This is a B0, enter its pT
    cout << "Filling B0 pT" << endl;
    B0mesonPt->Fill(pythia.event[Daughter].pT());
      }
      Vec4 daughterVec4 = pythia.event[Daughter].p();
      double daughterRap = myRapidity(daughterVec4);

       if (pythia.event[Daughter].id()==-521) {
    // This is a Bminus, enter its pT
    cout << "Filling Bminus pT" << endl;
    BminusmesonPt->Fill(pythia.event[Daughter].pT());
    if (fabs(daughterRap)<1.0) {
      BminusmesonPtCDFrap->Fill(pythia.event[Daughter].pT());
    }
      }
      if (pythia.event[Daughter].id()==521) {
    // This is a Bplus, enter its pT
    cout << "Filling Bplus pT" << endl;
    BplusmesonPt->Fill(pythia.event[Daughter].pT());
    if (fabs(daughterRap)<1.0) {
      BplusmesonPtCDFrap->Fill(pythia.event[Daughter].pT());
    }
      }

      int nextDaughter1 = pythia.event[Daughter].daughter1();
      int nextDaughter2 = pythia.event[Daughter].daughter2();
      // search for electron or positron
      for (int iDaughter = nextDaughter1; iDaughter<=nextDaughter2; ++iDaughter) {
    //cout << "daughter is a " << pythia.event[iDaughter].name() << endl;
    if (pythia.event[iDaughter].id()==11) {
      cout << "Found electron" << endl;
      cout << pythia.event[iDaughter].name() << endl;
      electronIndex=iDaughter;
      electronFrombPt->Fill(pythia.event[electronIndex].pT());
      break;
    }
    if (pythia.event[iDaughter].id()==-11) {
      cout << "Found positron" << endl;
      cout << pythia.event[iDaughter].name() << endl;
      positronIndex=iDaughter;
      positronFrombPt->Fill(pythia.event[positronIndex].pT());
      break;
    }
      }// loop over daughters to check for e+e-
     
      // If we get here, that means there were no electrons nor positrons.
      // Set the Daughter index to zero now.
      Daughter = 0;
      // If any of the daughters is still a beauty-hadron, we can try again
      // and reset the Daughter index, but only if one of the daughters contains a
      // b quark.
      for (int jDaughter = nextDaughter1; jDaughter<=nextDaughter2; ++jDaughter) {
    if (isBHadron(pythia.event[jDaughter].id())) {
      //One of the daughters is a beauty hadron.
      Daughter = jDaughter;
    }
      }// loop over daughters to check for another b hadron
    }//end of search for electron among daughters of bbar quark
   
    if (electronIndex!=0 && positronIndex!=0) {
      cout << "Found an e+e- pair from bbar" << endl;
      cout << "Ele 4-mom = " << pythia.event[electronIndex].p() << endl;
      cout << "Pos 4-mom = " << pythia.event[positronIndex].p() << endl;
      Vec4 epluseminus(pythia.event[electronIndex].p()+pythia.event[positronIndex].p());
      epluseminusMinv->Fill(epluseminus.mCalc());
      double epluseminusRap = 0.5*log((epluseminus.e()+epluseminus.pz())/(epluseminus.e()-epluseminus.pz()));
      epluseminusRapidity->Fill(epluseminusRap);
      if (fabs(epluseminusRap)<0.5) epluseminusMinvMidRap->Fill(epluseminus.mCalc());
    }
    else {
      cout << "No e+e- pair in event" << endl;
    }
   
  // End of event loop. Statistics. Histogram. Done.
  }// event loop
  if (showStat) pythia.statistics();
  //cout << mult << endl;

  //Write Output ROOT hisotgram into ROOT file
  TFile* outFile = new TFile("pythiaOutputHistosTest.root","RECREATE");
  multHist->Write();
  bquarkPt->Write();
  bbarquarkPt->Write();
  B0mesonPt->Write();
  B0barmesonPt->Write();
  BplusmesonPt->Write();
  BminusmesonPt->Write();
  BplusmesonPtCDFrap->Write();
  BminusmesonPtCDFrap->Write();
  electronFrombPt->Write();
  positronFrombPt->Write();
  epluseminusMinv->Write();
  epluseminusRapidity->Write();
  epluseminusMinvMidRap->Write();
  outFile->Close();

  return 0;
}
 

Varying the Continuum Contribution to the Dielectron Mass Spectrum

Initial Normalization

The normalization to the Drell-Yan and b-bbar cross sections are given by the calculation from Ramona in the Drell-Yan case and by Pythia in the b-bbar case.  There is an uncertainty in the overall normalization of the contribution from these two sources to the dielectron continuum under the Upsilon peak.  We can do a fit to obtain the Upsilon yield with the normalization fixed.  This is shown below.

Fig. 1: Fit to the invariant mass spectrum.  The data points are in blue. The Drell-Yan curve is the dot-dashed line and the b-bbar is the dashed line.  The Red line is the sum of the Upsilon line shape (obtained from embedding for the 1S+2S+3S keeping their ratios according to the PDG values) plus the continuum contribution from DY+b-bbar.  The red histogram is the integral of the red line, which is what is used to compare to the data in the fit (we fit using the "i" option to use the integral of the function in each bin).

With the above fit, we obtain 64.3 counts after integrating the upsilon part (the yield of DY is 32.3 and the yield of b-bbar is 26.8, both are held fixed for the fit). This gives a cross section of 63.4/(1*0.054*9.6 pb-1) = 124 pb.  The efficiency estimate of 5.4% for the overall efficiency is still being checked though, given the E/p shape not being gaussian due to the trigger bias near the L0 threshold, so this can still change.

It is also possible to let the yield of the continuum vary and study if the chisquare/dof of the fit improves.  That way, we can not just assume a continuum yield, but actually measure it.  Since the yields of the DY and the b-bbar are very similar and given our statistics we can't really discriminate one from the other, we are mainly sensitive to the sum.  One way to study this is to keep their ratios fixed as in the plot above, but vary the overall yield of both of them  This adds one extra parameter to the fit to account for the total sum of the continuum yield.  We perform the fit in the region 5< m < 16 GeV/c2.

One issue is that the Crystal-Ball fit is a user defined function, and we use the integral of the function to fit, which seems to push ROOT to its limit in an interactive session with a macro interpreted on the fly.  This is alleviated somewhat by cleaning up the code to do the one-parameter fit in a compiled macro.  However, trying out the two-parameter fit directly seems to be too much for ROOT even in compiled mode and the code runs out of memory and seg-faults.  A (rather inelegant) way around this is to scale the continuum yield by hand, compile the macro each time and do the one-parameter fit. For each of those fits, one can obtain the chisquare/deg. of freedom.  This is shown in the plot below:

Fig. 2. Chisquare per degree of freedom as a function of the continuum yield (Drell-Yan + b-bbar).

We find a clear minimum, indicating that our data do have some sensitivity to the continuum yield.  The Rightmost point with 59.1 counts is the yield obtained directly from Pythia 8.108 and from Ramona's calculation.  Our data indicate that the yield is likely smaller by about a factor of 2, we obtain at the minimum a yield of 26.6 counts.  Since the yield of Upsilons is obtained from the same fit, our fitted Upsilon yield will increase with decreasing counts from the continuum.  This is shown below.

Fig. 3: Fitted yield of Upsilons for a given continuum yield.  The minimum found above is illustrated by the vertical line.

The corresponding plot with the fit at the minimum is shown below.

Fig. 4: Dielectron data with the curves for the DY and b-bbar at the yield which minimizes the chi-square.  In other words, the result of a (poor man's) two-parameter fit to find both the Upsilon yield and the Continuum yield.

The results of this fit give 14.5 counts for DY and 12.1 counts for b-bbar, i.e a factor 0.45 lower than the 32.3 counts for DY and the 26.8 counts for b-bbar is 26.8 obtained before.  Ramona's calculation for dsigma/dm |y|<1 gave 5.25 nb and the Pythia cross section b-bbar cross section times the BR into e+e- gives 6.5 nb, so our data indicate that we can decrease these by a factor 0.45 (or decrease one by essentially 100% and leave the other one unchanged).  The Upsilon yield in this case increases to 92.1 counts, which gives a cross section of 92.1/(1*0.054*9.6) = 178 pb.  So this has a large effect on the yield (92.1-64.338)/92.1 = 0.3, i.e. a 30% change in the yield (and hence in the cross section).  Note also that 178 pb is quite larger than our first estimate for the cross section.  This highlights the importance of getting the efficiency estimates right.

 

WWW

Heavy Flavor Lepton

Heavy flavor leptons provide an extra handle on the open heavy flavor mesons, since they come from semi-leptonic decays of D and B mesons with significant branching ratios. Once produced, leptons do not participate in the strong interaction in the later stages of the collision, and remain a clean probe into the whole evolution of the system. Apart from TPC and TOF, BEMC is used to improve electron identification, and MTD is used for muon detection.

Heavy flavor muons

Non-photonic electrons

Hidden Heavy Flavor

J/psi suppression was one of the proposed QGP signatures in the early days. Later, various cold nuclear matter effects were brought up to complicate the interpretation of J/psi measurements. Still, the study of J/psi collective motion deepens our understanding of the coalescence mechanism and the charm quark collectivity. We also reconstructed Upsilon and observed the suppression of Upsilon(1S+2S+3S).

J/psi

Upsilon

Open Heavy Flavor

More than 99% of charm quarks hadronize into open charm, D mesons. So the measurement of D mesons is a must for the determination of charm cross section. Due to the short life time, the low production rate and the high combinatorial background, the direct reconstruction of D mesons is difficult with the TPC pointing resolution. HFT will be employed to reconstruct the displaced vertex and greatly suppress the combinatorial background. This will also enable the D0 flow analysis, to ascertain the charm quark collectivity. Other open heavy flavor hadrons like Ds and Lambdac will also be studied with HFT.

D mesons

Jet-like correlations

 

A jet is a spray of hadrons produced by the “hard” scattering of a parton (quark or gluon). A hard scattering is one in which a large amount of energy is transferred between partons.

Hard scatterings occur early in a heavy-ion collision, allowing the scattered partons to act as probes of the medium created in these collisions.

The modifications of jets measured in Au+Au collisions compared to p+p collisions is interpreted to be an effect of the large densities in Au+Au collisions.  Such modifications have been measured in a variety of observables. 

 
  - Suppression of hadrons measured at high transverse momentum (pT)

  - Suppression of the away-side jet measured in 2-particle correlations, when selecting a high pT trigger particle
 
 
Ongoing analyses in this Physics Working Group focus on correlations measured between particles to further understand jet modifications in the medium produced in Au+Au collisions.  Such analyses include:
  - Untriggered 2-particle correlation measurements in 2 dimensions
  - Particle-identified particle correlations
  - 2+1 correlation measurements
  - Direct-photon-triggered correlations
  - Studies of the long range correlation in pseudorapidity observed in central Au+Au collisions
  - Full jet reconstruction
  - High pT single-particle hadron measurements at lower beam energies

 

Event Structure

Event structure focus group Pages

EStruct Home Page

Welcome to the STAR Event Structure Home Page!

Some of the methods commonly used in EStruct are described in the Tutorials (public).  Conference and seminar talks are linked from Talks (public) and publications are found Publications (public).  To see our work in progress visit You do not have access to view this node (internal).

 

Publications

 

Links to the papers in public

Publications

Two-particle correlations on transverse momentum and minijet dissipation in Au-Au collisions at $\sqrt{s_{NN}} = 130$ GeV
J. Phys. G 34 (2007) 799, and nucl-ex/0408012

The energy dependence of $p_{\rm t}$ angular correlations inferred from mean-$p_{\rm t}$ fluctuation scale dependence in heavy ion collisions at the SPS and RHIC
J. Phys. G 34 (2007) 451, and nucl-ex/0605021

The multiplicity dependence of inclusive pt spectra from p-p collisions at $\sqrt{s}$ = 200 GeV
Phys. Rev. D 74, 032006 (2006), and nucl-ex/0606028

Transverse-momentum pt correlations on momentum subspace (eta,phi) from mean-pt fluct uations in Au-Au collisions at 200 GeV
J. Phys. G 32 (2006) L37, and nucl-ex/0509030

Minijet deformation and charge-independent two-particle correlations on momentum subspace $(\eta,\phi)$ in Au-Au collisions at $\sqrt{s_{NN}}$ = 130 GeV
Phys. Rev. C 73 (2006) 064907, and nucl-ex/0411003

Hadronization geometry and charge-dependent two-particle correlations on momentum subspace ($\eta,\phi$) in Au-Au collisions at $\sqrt{s_{NN}} = 130$ GeV
Phys. Let. B 634 (2006) 347, and nucl-ex/0406035

Event-wise fluctuations in Au-Au collisions at sqrt(s[sub NN])=130 GeV
Phys. Rev. C 71 (2005) 064906, and nucl-ex/0308033

Transverse-momentum dependent modification of dynamic texture in central Au+Au collisions at sqrt(sNN ) = 200 GeV
Phys. Rev. C 71 (2005) 031901(R), and nucl-ex/0407001
 

From ES PWG Group members

Publications

Azimuth quadrupole component spectra on transverse rapidity y[sub t] for identified hadrons from Au-Au collisions at sqrt(s[sub NN]) = 200 GeV by T. A. Trainor
Phys. Rev. C 78, 064908 (2008)

Autocorrelations from fluctuation scale dependence by inversion by T. A. Trainor, R. J. Porter and D. J . Prindle
J. Phys. G 31 809-824, and hep-ph/0410182

Transverse-momentum $p_t$ correlations from mean-$p_{t}$ fluctuation scale dependence in Hijing-1.37-simulated Au-Au collisions at $\sqrt{s_{NN}} = $ 200 GeV by Qingjun Liu, Duncan J. Prindle, Thomas A. Trainor
Phys. Let. B 632 197, and hep-ph/0410180

Extrapolating parton fragmentation to low $Q^2$ in $e^+$-$e^-$ collisions by T. A. Trainor and D. Kettler
Phys. Rev. D 74, 034012 (2006), and hep-ph/0606249
 

Proceedings

Low-Q^2 partons in p-p and Au-Au collisions at XXXV International Symposium on Multiparticle Dynamics 2005 (ISMD2005) by T. A. Trainor

Transverse momentum correlations in relativistic nuclear collisions invited talk at Correlations and Fluctuations in Relativistic Nuclear Collisions Workshop (MIT, 2005) by T. A. Trainor

Probing the bulk medium in relativistic heavy ion collisions using two-particle correlations invited talk at Correlations and Fluctuations in Relativistic Nuclear Collisions Workshop (MIT, 2005) by R. L. Ray

The equivalence of fluctuation scale dependence and autocorrelations invited talk at Correlations and Fluctuations in Relativistic Nuclear Collisions Workshop (MIT, 2005) by D. J. Prindle and T. A. Trainor

Correlations from p-p collisions at sqrt(s) = 200 GeV invited talk at Correlations and Fluctuations in Relativistic Nuclear Collisions Workshop (MIT, 2005) by R. J. Porter and T. A. Trainor

Correlation structure of STAR events plenary talk at the International Conference on Contemporary Issues in Nuclear and Particle Physics (CINPP 2005) by Mikhail Kopytine

Correlations in STAR: interferometry and event structure plenary talk at the 5th International Conference on Physics and Astrophysics of Quark Gluon Plasma (ICPAQGP-2005) by Mikhail Kopytine

"Event Structure at RHIC from p-p to Au-Au," at the 20th Winter Workshop on Nuclear Dynamics (2004) by Tom Trainor (hep-ph/0406116)

"Soft and hard components of two-particle distributions on (yt,eta,phi) from p-p collisions at sqrt(s)=200 GeV" at QM2004 by R.J. Porter, T.A. Trainor

Long range hadron density fluctuations at soft pT in Au+Au collisions at RHIC invited talk at Xth International Wokshop on Multiparticle Production (Correlation and Flucutations in QCD) by Mikhail Kopytine

Correlations, Fluctuations, and Flow Measurements from the STAR Experiment at Quark Matter 2002 by Lanny Ray


Preprints

A power-law description of heavy-ion collision centrality by Thomas A. Trainor and Duncan J. Prindle (hep-p h/0411217)

Extrapolating parton fragmentation to low Q^2 in e+e- collisions by Thomas A. Trainor and David T. Kettler (hep-ph/0606249)

What Does the Balance Function Measure? by Thomas A. Trainor (hep-ph/0301122)

Jet quenching and event-wise mean-pt fluctuations in Au-Au collisions at sqrt-sNN = 200 GeV in Hijing-1.37 by Qingjun Liu, Thomas A. Trainor (hep-ph/0301214)

Event-by-Event Analysis and the Central Limit Theorem by T.A. Trainor (hep-ph/000114)

Pion Lattices in HI Transverse Phase Space and Sudden Traversal of the QCD Phase Boundary by T.A. Trainor (hep-ph/0005176)

Jet Correlations and Scale-Local Measures by T.A. Trainor and J.G. Reid

Probing small length scales in heavy-ion collisions with event-by-event correlation analysis by T.A. Trainor (hep-ph/0004258)
 

Theses

M. Daugherity

A. Ishihara(ps)

J.G. Reid

Talks

Presentations

2009

DNP: Hawaii - Lanny Ray
DPF: Detroit - Chanaka De Silva
Ultra-Relativistic Nucleus-Nucleus Collisions: Knoxville - Duncan Prindle

2008

Tamura Symposium: Austin - Lanny Ray
DNP: Oakland - Duncan Prindle
DNP: Oakland - Lanny Ray
Workshop for young scientists: Ultra-Relativistic Nucleus-nucleus collisions: Estes Park, CO - David Kettler
Users meeting: Upton, NY - Tom Trainor
Winter Workshop: South Padre, TX - Lanny Ray
QM08: Jaipur, India - Michael Daugherity

General in 2006

Spring APS Meeting - Lanny Ray (ppt)
Spring APS Meeting - Michael Daugherity (ppt)

Quark Matter 05

Bulk-medium Properties in Relativistic Nuclear Collision - Duncan Prindle
Dissipation and Fragmentation of Low-Q^2 scattered partons at RHIC - Lanny Ray (ppt)
Two-particle Correlations from p-p Collisions at 200 GeV - Tom Trainor

General in 2005

ISMD 2005 - Tom Trainor
MIT Workshop on Correlations and Fluctuations - Jeff Porter
MIT Workshop - Duncan Prindle
MIT Workshop - Lanny Ray (ppt)
MIT Workshop - Tom Trainor
RHIC-AGS User's Meeting, June 2005 - Lanny Ray
RHIC-AGS User's Meeting, June 2005 - Tom Trainor

DNP meeting 04, Chicago

Lanny Ray
Michael Daugherity

General in 2004

Physics colloquium at Rice U. - Lanny Ray (Oct)
Nuclear physics seminar at BNL - Mikhail Kopytine (Sept)
ISMD 2004 - Jeff Porter
GSI Workshop, Skopelos, Greece - Tom Trainor
RHIC-AGS User's Meeting, May 2004 - Tom Trainor
20th Winter Workshop on Nuclear Dynamics, Jamaica, - Tom Trainor

DNP meeting 04, Chicago

Daugherity
Lanny Ray

General in 2004

Physics colloquium at Rice U. - Lanny Ray (Oct)
Nuclear physics seminar at BNL - Mikhail Kopytine (Sept)
ISMD 2004 - Jeff Porter
GSI Workshop, Skopelos, Greece - Tom Trainor
RHIC-AGS User's Meeting, May 2004 - Tom Trainor
20th Winter Workshop on Nuclear Dynamics, Jamaica, - Tom Trainor

Quark Matter 04

Porter
Lanny Ray

DNP meeting 03, Tucson

Aya Ishihara
Porter
Lanny Ray

General in 03

Talk given at Ohio State U. by Lanny Ray (ppt)

Tutorials

Event Structure Tutorials


This page contains tutorials written to document and explain Event Structure analysis techniques and results.

 

Tutorial Title Files
Tutorial 1
Understanding charge independent correlations on eta1-eta2 versus phi1-phi2 for proton-proton di-jet events ppt | pdf
Tutorial 2
Measuring Histograms of the Number of Pairs of Particles, Constructing Ratios of Histograms, and the relationship to Correlations – Part 1 ppt | pdf
Tutorial 3
Measuring Histograms of the Number of Pairs of Particles, Constructing Ratios of Histograms, and the relationship to Correlations – Part 2 ppt | pdf
Tutorial 4
Relating Fluctuations and Correlations – Part 1 ppt | pdf

 

Tutorials by Lanny Ray, ray@physics.utexas.edu

 

HI jet finding

The Heavy Ion jet finding is a cross PWG discusison group and relates to the jet-like correlation PWG.

Updates can be found at the wiki-pages: http://rnc.lbl.gov/wiki/index.php/STAR_Jet_Reconstruction_in_Heavy_Ion_Collisions 

This activity group is lead by Joern Putschke.

High pT

High Pt is a focus activity group of Jet-like correlations PWG

 For further details see the protected area: www.star.bnl.gov/protected/jetcorr/

JetCorr Data QA

The contents of this page include dataset QA and run and tower selections and corresponding discussions shared by JetCorr PWG.

Data-

  • Run6 pp
    • Bad Run list
    • Bad Tower list
  • Run7 AuAu (dataset QA plots will be linked here in the near future)
    • Bad Run list
    • Bad Tower list
  • Run11 AuAu (dataset QA plots will be linked here in the near future)
    • Bad Run list
    • Bad Tower list
  • Run12 pp P12id  (dataset QA plots will be linked here in the near future)
  • Run14 AuAu P18ih
  • Run15 pAu P16id (dataset QA link will be linked here in the near future)

Simulations and Embedding -

Tracking Efficiencies -
Run14 AuAu /star/u/elayavalli/WORK/ANALYSIS/Run14TrackingEfficiency/Run14_AuAu_200_tracking_efficiency_and_momentum_smearing_dca_3p0(1p0, 2p0)_nhit_20(15)_nhitfrac_0p52.root
The histograms you need are
hTrack_(species - pion, kaon, proton)_Efficiency_pTEta_final_centbin#_lumibin# where centbin goes from 0 - 0-5% to 15 - 75-80%  and lumibin 0 - 0-10kHz and 9 - 90-100kHz - they are averaged for particle/anti-particle.
there are also track resolution histograms appropriately named for each species
the plot_eff.C macro produces these files and also draw some plots so you can also look at the naming there as well.

Run14 AuAu P18ih

  • In P18ih, the tracking issues reported in previous productions (P17id, P18if) of Run14 Au+Au data are fixed. The corresponding discussions can be found in Daniel Nemes's presentation on 3 May, 2019 (link). 
  • Primary tracks in this production (P18ih) were reconstructed without HFT hits, while P16id production included HFT hits for the primary track reconstruction. 
  • Run14 AuAu P18ih run list
  • Run14 AuAu P18ih tower list

Other Groups

 

Focus groups, special topics or activity groups are NOT Physics Working Group (PWG) and hence, do not have publications or paper authorities.

Many of those topics are however of general interrest for a few PWG. The relation between activity groups and the respective PWG will be documented here as groups are created.

Parity violation

STAR search for local strong parity violation in heavy ion collisions


Group members:

  • Wayne State U.
    Sergei Voloshin (bulkcorr/ebye)
  • Indiana U.
    Ilya Selyuzhenkov (drupal)
  • BNL
    Vasily Dzordzhadze (wasikos)
    Ron Longacre
    Yannis Semertzidis
    Paul Sorensen
  • UCLA
    Dhevan Gangadharan (bulkcorr)
    Gang Wang (bulkcorr)
  • Yale U.
    Jack Sandweiss
    Evan Finch (bulkcorr)
    Alexey Chikanian
    Richard Majka
  • LBNL
    Jim Thomas (jhthomas)
  • MEPhI
    Vitaly Okorokov

 

Parity group meetings

2010 meetings

September 22, 14:00-15:30 EST: EVO meeting information


2009 meetings

September 24, 14:00-15:30 EST; 510-486-7720

September 10, 14:00-15:30 EST; 510-486-7720

September 03, 14:00-15:30 EST; 510-486-7720

August 13, 14:00-15:30 EST; 510-486-7720

July 23, 14:00-15:30 EST; 631-344-2261

July 16, 14:00-15:30 EST; 631-344-2261

June 18, 14:00-15:30 EST; 631-344-2261

June 04, 14:00-15:30 EST; 631-344-2261

May 28, 14:00-15:30 EST; 631-344-2261

May 21, 14:00-15:30 EST; 631-344-2261

May 14, 14:00-15:30 EST; 631-344-8261

April 30, 14:00-15:30 EST; 631-344-2261

April 23, 14:00-15:30 EST; 631-344-2261

April 16, 14:00-15:30 EST; 631-344-2261

April 9, 14:00-15:30 EST; 631-344-2261

March 19, 14:00-15:30 EST; 631-344-8261

March 12, 14:00-15:30 EST; 631-344-2261

March 5, 14:00-15:30 EST; 631-344-2261

February 26, 14:00-15:30 EST; 631-344-2261

February 19, 14:00-15:30 EST; 631-344-2261

February 12, 14:00-15:30 EST; 631-344-2261

February 05, 14:00-15:30 EST; 631-344-2261

January 29, 14:00-15:30 EST; 631-344-2261

January 22, 14:00-15:30 EST; 631-344-2261

January 15, 14:00-15:30 EST; 631-344-2261

January 08, 14:00-15:30 EST; 631-344-6363


2008 meetings

December 22, 15:00pm; EVO STAR/parity room

December 15, 15:30pm EVO STAR/parity room

December 08, 11:00am EVO STAR/parity room

December 01, 11:00am phone 631-344-2261

November 21, 12:00pm phone 631-344-8261

November 05, 1:30pm phone 631-344-2261

October 20, 3:30pm phone 631 344 2261

September 24, 4:00pm phone 631 344 6261

September 16, 10:00am phone 631 344 2261

July 1, 10:30AM phone 877 322 9648, the participant code is 298859.

May 30, 1:30-3:00pm phone 631 344 6261

March 29, 11:00AM-5:00pm phone 631 344 6261 BNL meeting, Room 1-188

January 17, 4:00pm phone 631 344 6363


2007 meetings (list incomplete)

December 25, 2:00pm phone 631 344 8383

Parity paper proposal

Azimuthal Charged-Particle Correlations
and Possible Local Strong Parity Violation

Published in Phys. Rev. Lett. 103, 251601 (2009)

Abstract
Parity-odd domains, corresponding to nontrivial topological solutions of the QCD vacuum,
might be created during relativistic heavy-ion collisions.
These domains are predicted to lead to charge separation of quarks along the system’s orbital momentum axis.
We investigate a three-particle azimuthal correlator which is a P even observable,
but directly sensitive to the charge separation effect.
We report measurements of charged hadrons near center-of-mass rapidity
with this observable in Au+Au and Cu+Cu collisions at √sNN=200  GeV using the STAR detector.
A signal consistent with several expectations from the theory is detected.
We discuss possible contributions from other effects that are not related to parity violation.


Observation of charge-dependent azimuthal correlations
and possible local strong parity violation in heavy-ion collision

Published in Phys. Rev. C 81, 054908 (2010)

Abstract
Parity (P)-odd domains, corresponding to nontrivial topological solutions of the QCD vacuum,
might be created during relativistic heavy-ion collisions.
These domains are predicted to lead to charge separation of quarks
along the orbital momentum of the system created in noncentral collisions.
To study this effect, we investigate a three-particle mixed-harmonics azimuthal correlator
which is a P-even observable, but directly sensitive to the charge-separation effect.
We report measurements of this observable using the STAR detector in Au+Au and Cu+Cu collisions at √sNN=200 and 62 GeV.
The results are presented as a function of collision centrality,
particle separation in rapidity, and particle transverse momentum.
A signal consistent with several of the theoretical expectations is detected in all four data sets.
We compare our results to the predictions of existing event generators and
discuss in detail possible contributions from other effects that are not related to P violation.


Data & figures


Principal authors

  • Wayne State: Sergei Voloshin
  • Indiana: Ilya Selyuzhenkov
  • BNL: Vasily Dzordzhadze, Ron Longacre, Yannis Semertzidis, Paul Sorensen
  • UCLA: Gang Wang, Dhevan Gangadharan
  • Yale: Jack Sandweiss, Evan Finch, Alexey Chikanian, Richard Majka
  • LBNL: Jim Thomas
  • MEPhI: Vitaly Okorokov

GPC members

  • Carl Gagliardi, Chair
  • Ernst Sichtermann, Member
  • Peter Seyboth, Member
  • Mike Lisa, PWG representative
  • Spencer Klein, English/Grammar QA
  • Jin-Hui Chen, Analysis Code QA
  • Sergei Voloshin, PA Representative
  • Jack Sandweiss, PA Representative

Collaboration Comments

GPC Comments


Support document


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PRC data

Data points and figures for the paper titled:
"Observation of charge-dependent azimuthal correlations and
possible local strong parity violation in heavy ion collisions
"

Figure 1: png, eps

Figure 2a: macro, png, eps

cos(a+b-2c)*RefMult (Au+Au@200GeV, RFF)
RefMult a+,b+,c- stat err a-,b-,c- stat err a-,b-,c+ stat err a+,b+,c+ stat err a+,b-,c- stat err a+,b-,c+ stat err
15 -0.00232407 0.000829793 0.000119327 0.00138676 -0.000155248 0.000836209 0.000377743 0.00134908 0.00231604 0.000591495 0.00114578 0.000585172
45 -0.00220487 0.000277435 -0.00154608 0.000300603 -0.00166599 0.000281433 -0.0014893 0.000290075 0.00020804 0.000198749 0.000580582 0.000196687
75 -0.00224734 0.000235853 -0.00207896 0.000248034 -0.00228668 0.000241471 -0.00231991 0.000239425 0.00036892 0.000170228 0.000448703 0.000168455
105 -0.00289638 0.000226039 -0.00233147 0.000236072 -0.00241574 0.000230331 -0.0026543 0.000227916 0.000387332 0.000163583 0.000249001 0.000161912
135 -0.00262571 0.000222697 -0.00235069 0.000230554 -0.00296293 0.000226604 -0.00291115 0.000223666 0.000210685 0.000160256 6.98659e-05 0.00015921
165 -0.00279487 0.000218518 -0.00256624 0.000226913 -0.00262333 0.000224352 -0.00291613 0.000220794 -0.000146566 0.000159207 9.08978e-05 0.000158999
195 -0.00295961 0.000219526 -0.00246627 0.000226296 -0.00275933 0.000224655 -0.0028007 0.000219746 1.59922e-05 0.000158547 8.94614e-05 0.000159038
225 -0.00260667 0.000214571 -0.00231615 0.000223414 -0.00217615 0.000219907 -0.00258728 0.000215569 -0.000133701 0.000157142 -3.46813e-06 0.000156503
255 -0.00192389 0.000215148 -0.00231561 0.000219962 -0.00208204 0.000219112 -0.00221258 0.000212905 0.000163299 0.000154749 0.000284978 0.000154216
285 -0.00219529 0.000208311 -0.00166138 0.000216016 -0.00199152 0.000213699 -0.00186841 0.000207701 -6.27691e-05 0.000152382 1.29396e-05 0.000150959
315 -0.00270664 0.000205232 -0.00209181 0.000212923 -0.00192307 0.000210769 -0.0021717 0.000204519 -0.000295788 0.000149399 -0.000228133 0.000148715
345 -0.00180793 0.000199707 -0.0015465 0.000206451 -0.00106008 0.000205592 -0.00122987 0.00019939 -0.000131745 0.000145381 0.000203784 0.000146057
375 -0.00168947 0.000198789 -0.00153055 0.000205673 -0.0011612 0.000202903 -0.00167602 0.000197431 -0.000356638 0.000146453 -7.43794e-05 0.000144508
405 -0.00143713 0.000191464 -0.00121617 0.000197463 -0.000904646 0.000195544 -0.00141614 0.000190911 -0.000269779 0.000140161 4.65348e-05 0.00013893
435 -0.00108155 0.000188747 -0.00106764 0.000195579 -0.000813369 0.000192186 -0.0010527 0.000186647 -0.000391462 0.00013766 -0.000194741 0.00013675
465 -0.000745431 0.000182591 -0.000465976 0.000190779 -0.000162135 0.000189958 -0.000753386 0.000182575 -8.77953e-05 0.000134289 0.000120421 0.00013325
495 -0.000725871 0.000179685 -0.000680639 0.000186129 -0.000581522 0.000182518 -0.000663292 0.000176886 -0.000319672 0.000130575 5.32e-05 0.000128714
525 -0.000798782 0.000177661 -0.000672209 0.00018295 -0.000177874 0.000182432 -0.000499309 0.000175048 -0.000486717 0.00012978 -0.00021756 0.000129396
555 -0.000812354 0.000178516 -0.000743912 0.000185105 0.000146604 0.000181387 -0.000798392 0.000177413 -0.000344484 0.000130837 -5.04185e-07 0.000128817
585 -0.000538112 0.000193801 -0.00034451 0.000201309 0.000328942 0.000199141 -0.000354971 0.000191926 -0.000362969 0.000142144 3.15027e-05 0.000140287
615 -0.000615069 0.000246748 -0.000835844 0.000255874 6.13817e-05 0.000256199 -0.000508298 0.000245614 -0.00064337 0.00018173 -9.52957e-05 0.000180022
645 -0.000836006 0.000395658 -0.000938061 0.000412778 0.000594157 0.000405245 -0.000828964 0.000395171 -0.00061075 0.000295881 -0.000105171 0.000289835
675 -0.000507544 0.000915657 -0.00212875 0.000995109 -0.00113305 0.000952714 0.000193596 0.000840556 -0.0015933 0.000670818 -0.000423606 0.000637297

Figure 2b: macro, png, eps

cos(a+b-2c)*RefMult (Au+Au@200GeV, RFF)
RefMult a+,b+,c- stat err a-,b-,c- stat err a-,b-,c+ stat err a+,b+,c+ stat err a+,b-,c- stat err a+,b-,c+ stat err
15 -0.00119735 0.000782732 0.00141434 0.00130906 -0.00176007 0.000790662 0.000310067 0.00127807 0.00126299 0.000557027 0.0015828 0.00055348
45 -0.0018582 0.000261521 -0.00107675 0.000283461 -0.00145127 0.000265101 -0.00158609 0.000273429 0.000530898 0.000187481 0.000905114 0.000185466
75 -0.00266332 0.00022381 -0.00245264 0.000234264 -0.00288736 0.000226644 -0.00226594 0.000226426 0.000207821 0.000160527 0.000401931 0.000159358
105 -0.00307452 0.000214363 -0.00259794 0.000221475 -0.00254143 0.000216506 -0.00284109 0.000214977 0.000120955 0.000153917 -7.68965e-05 0.000152917
135 -0.00266785 0.000209746 -0.0029161 0.00021775 -0.00278005 0.000213925 -0.00251862 0.000209804 0.000311951 0.000151608 0.000345262 0.000149951
165 -0.00240619 0.000208276 -0.00248683 0.00021448 -0.00253635 0.000212185 -0.00253094 0.000208382 0.000179285 0.00015089 0.000178993 0.000149726
195 -0.00288223 0.000206074 -0.00257086 0.000211281 -0.00291019 0.000209375 -0.00280884 0.000205487 -0.000196658 0.000148795 -9.38108e-06 0.00014791
225 -0.00202028 0.000202762 -0.00272478 0.000209651 -0.0027715 0.000207847 -0.00257345 0.000202847 3.09283e-05 0.00014773 -5.2055e-06 0.000146131
255 -0.0021495 0.000201407 -0.00237099 0.000205874 -0.0022738 0.000205139 -0.00218616 0.000200559 0.000110512 0.000145917 -4.72896e-05 0.000145991
285 -0.00209165 0.000196196 -0.00190663 0.000202658 -0.00185677 0.000200848 -0.00203046 0.000196446 -6.56069e-05 0.000142769 -3.25727e-05 0.00014249
315 -0.00205665 0.000194764 -0.00196416 0.000199537 -0.00180705 0.000198055 -0.00193224 0.000196714 -1.34144e-05 0.000141358 5.5005e-05 0.000141089
345 -0.00158329 0.000190464 -0.00173496 0.000194188 -0.00152631 0.000192842 -0.00125894 0.00019119 -0.000199262 0.000137769 -2.91883e-06 0.000137282
375 -0.00138797 0.000186862 -0.00142499 0.000190709 -0.00145592 0.000191195 -0.001454 0.00018594 6.99359e-05 0.000135781 4.68298e-05 0.000135455
405 -0.000723951 0.000181713 -0.00100372 0.000185086 -0.00131307 0.000183369 -0.000940146 0.000180194 -7.51175e-06 0.000131871 -0.000139492 0.000131496
435 -0.000766659 0.000178159 -0.00105217 0.000180895 -0.00113949 0.000178557 -0.00136478 0.000176904 -6.56264e-05 0.000129327 -0.000363394 0.000127815
465 -0.000500216 0.000174094 -0.000538272 0.000177052 -0.00103208 0.000175118 -0.00112507 0.000173217 0.000155409 0.000127064 -0.000304409 0.000125367
495 -0.000257138 0.000173719 -0.000884924 0.000173404 -0.000674623 0.000172236 -0.00075774 0.000173421 0.000115562 0.000125306 -0.000285744 0.000124288
525 0.000282244 0.000170412 -0.000657846 0.000170241 -0.000822593 0.000168472 -0.0006236 0.000169028 -3.3225e-05 0.000122343 -0.000391094 0.000121394
555 0.000304678 0.00017222 -0.000187598 0.000172656 -0.000344014 0.000171608 -0.000933102 0.000172892 6.51062e-05 0.000124103 -0.000474486 0.000124162
585 0.000391631 0.00018731 -6.40869e-05 0.000187354 -0.000245166 0.000184335 -0.000729846 0.000186198 5.64022e-05 0.000134461 -0.000417892 0.000134246
615 0.000453731 0.000237114 -0.000511197 0.000236937 -0.000434279 0.00023581 -0.000488006 0.000239164 -0.000138194 0.000172102 -0.000487355 0.000170899
645 0.00048092 0.000389158 -0.000781413 0.000386339 -0.000576723 0.000384747 -0.000666297 0.000382087 -0.000148727 0.000279319 -0.00107329 0.000278086
675 7.2823e-05 0.000827774 -0.00260246 0.00087763 -0.00179739 0.000899376 -6.50901e-05 0.00086316 -0.000651071 0.000623772 -0.00149888 0.000614766

Figure 3a: macro, png, eps

cos(a+b-2c)*RefMult (Au+Au@200GeV, RFF)
RefMult a+,b+,c- stat err a-,b-,c- stat err a-,b-,c+ stat err a+,b+,c+ stat err a+,b-,c- stat err a+,b-,c+ stat err
15 -0.00172275 0.00080013 0.00165907 0.00131368 0.000623248 0.000805069 0.00101825 0.00128021 0.0020568 0.000572078 0.00143423 0.000565018
45 -0.00184205 0.000253366 -0.00137248 0.000271211 -0.00167964 0.000255719 -0.00131341 0.000262315 0.00047535 0.000181264 0.000593759 0.000179433
75 -0.0017237 0.000214724 -0.00172083 0.00022594 -0.00193095 0.000220501 -0.00184999 0.000217018 0.000503599 0.00015536 0.000695341 0.000153855
105 -0.00249692 0.000205677 -0.002206 0.000214344 -0.00215758 0.000209913 -0.00243708 0.000207611 0.000348464 0.000149361 0.000342232 0.000147678
135 -0.00234744 0.000202329 -0.00242401 0.000208794 -0.00263676 0.000205644 -0.00251081 0.000202884 0.000184445 0.000146182 6.77287e-05 0.000144767
165 -0.00259411 0.000198651 -0.00256004 0.000204897 -0.00258988 0.000203046 -0.00267324 0.000199282 -0.000216846 0.000144054 3.1985e-05 0.000143738
195 -0.00275157 0.000197799 -0.00238245 0.000203841 -0.00255781 0.000202404 -0.00257858 0.00019854 1.98542e-05 0.000143713 5.57649e-05 0.000143816
225 -0.00255286 0.000193256 -0.00219806 0.000200109 -0.00212405 0.000197985 -0.0025023 0.000193377 -0.000153767 0.000141089 -6.39296e-05 0.000140523
255 -0.00191495 0.000192857 -0.00211454 0.00019637 -0.00203684 0.000194866 -0.00207722 0.00018994 0.000260384 0.000138183 0.00031108 0.000137686
285 -0.0019354 0.000184943 -0.00156566 0.000193205 -0.00168024 0.000190711 -0.00181743 0.000184572 -4.06885e-05 0.000135843 -6.29732e-05 0.000134728
315 -0.00232949 0.000181081 -0.00197387 0.000186944 -0.00192706 0.000184839 -0.0020693 0.000179979 -0.000316019 0.000132067 -0.000196438 0.000130973
345 -0.00162844 0.000174959 -0.00151572 0.000180517 -0.00109926 0.000179934 -0.00111012 0.000175306 -0.000137866 0.000128057 9.17983e-05 0.000127926
375 -0.00142334 0.000172901 -0.00160589 0.000177349 -0.00137596 0.000174989 -0.00147865 0.000171104 -0.000217888 0.00012668 -0.000194052 0.000125739
405 -0.00122003 0.000164159 -0.00125859 0.000168965 -0.00108917 0.000166651 -0.00120248 0.000163803 -0.000165251 0.000119772 -3.53924e-05 0.000118757
435 -0.000999969 0.000160169 -0.00105981 0.000165419 -0.00100698 0.000163364 -0.00088948 0.000157516 -0.000369654 0.000116865 -0.000169475 0.000115996
465 -0.000731868 0.000152685 -0.000522984 0.000159238 -0.000384282 0.000158023 -0.000650514 0.000152166 -1.79267e-05 0.000112672 -3.74745e-05 0.000111044
495 -0.000692461 0.000147495 -0.000498443 0.000152654 -0.00046779 0.000148815 -0.000659678 0.000146515 -0.000138287 0.000107551 8.08487e-06 0.000105915
525 -0.000739136 0.000142542 -0.00082652 0.000149037 -0.000758062 0.000147502 -0.000509381 0.000142102 -0.000316743 0.000105259 -0.000413837 0.000104866
555 -0.000636739 0.000141059 -0.00049867 0.000146224 -0.000193691 0.000143602 -0.000599764 0.000139508 -6.71995e-05 0.000103376 -5.38327e-05 0.000101604
585 -0.000293866 0.000152146 -0.000116871 0.000155705 -0.000125367 0.000153155 -0.000158577 0.000149401 7.30972e-05 0.000111202 -3.06928e-05 0.000109161
615 -0.000531198 0.000190419 -0.000132553 0.000195378 -9.22203e-05 0.00019175 -8.14068e-05 0.000187112 -0.000117715 0.000138276 -2.34579e-05 0.000137477
645 -0.000562601 0.000304131 -0.000603966 0.000311056 -0.000124474 0.000307131 -0.000472886 0.000295348 -8.88681e-05 0.000222064 -8.7338e-05 0.000219847
675 0.000284921 0.000671082 -0.00048365 0.000740911 -0.000763021 0.000695172 0.000479815 0.000637069 -0.000553213 0.000498871 -0.000215109 0.000465702

Figure 3b: macro, png, eps

cos(a+b-2c)*RefMult (Au+Au@200GeV, RFF)
RefMult a+,b+,c- stat err a-,b-,c- stat err a-,b-,c+ stat err a+,b+,c+ stat err a+,b-,c- stat err a+,b-,c+ stat err
15 -0.00118288 0.000755492 0.00274672 0.00124016 -0.000884598 0.000764089 0.00178695 0.00121319 0.00160047 0.000540179 0.00152158 0.000537114
45 -0.00163536 0.000238416 -0.000880577 0.000256172 -0.00116532 0.000241473 -0.00123104 0.000247839 0.000771328 0.00017099 0.00101416 0.000169477
75 -0.00230374 0.000203753 -0.00197382 0.000213289 -0.00244431 0.000206742 -0.0019197 0.000205936 0.000274842 0.000146817 0.000526298 0.000145411
105 -0.00274132 0.000195059 -0.00233448 0.000201449 -0.00217374 0.000197538 -0.00240529 0.000195354 0.00018413 0.000140308 0.000149645 0.000139566
135 -0.00235453 0.000190212 -0.00266574 0.000197239 -0.00266811 0.000194276 -0.00216806 0.000190129 0.000163381 0.000137552 0.000352872 0.000136433
165 -0.0022777 0.000188946 -0.00230513 0.0001945 -0.00233791 0.000192771 -0.00230662 0.000188625 0.00031497 0.0001368 0.000200835 0.000136325
195 -0.00258776 0.000185729 -0.00235919 0.000190521 -0.00253062 0.000189622 -0.00266492 0.000185225 -0.000175253 0.000134631 -2.07776e-05 0.000134228
225 -0.00210831 0.000182691 -0.00269069 0.000188609 -0.00253593 0.000186594 -0.00239405 0.000182461 -9.23975e-05 0.000133059 5.45061e-06 0.000131511
255 -0.00220433 0.000179216 -0.00229314 0.000183813 -0.00189769 0.000182315 -0.0021816 0.000178635 8.62471e-05 0.000131135 -3.98901e-05 0.00013006
285 -0.00200888 0.000173383 -0.00178068 0.000180191 -0.00178207 0.00017847 -0.0021439 0.000173574 8.59283e-06 0.000126951 -6.65482e-06 0.000126458
315 -0.00214803 0.000171576 -0.00180103 0.000175843 -0.0016704 0.00017495 -0.00184886 0.000171578 -0.000293117 0.000124775 -3.07117e-05 0.000124491
345 -0.00150578 0.00016581 -0.00155606 0.000169969 -0.00149854 0.000168561 -0.00138956 0.000166453 -0.000305176 0.00012111 -3.74732e-05 0.000120748
375 -0.00138984 0.000160639 -0.00144675 0.000165994 -0.00134193 0.000165593 -0.00127677 0.000160941 -8.14137e-05 0.000117861 7.185e-05 0.000117081
405 -0.00106732 0.000155193 -0.000853155 0.000160479 -0.00132125 0.00015863 -0.00117253 0.000154124 -0.000169148 0.00011341 -0.000198113 0.000113296
435 -0.00096973 0.00015061 -0.00110841 0.00015356 -0.000978545 0.000152016 -0.00124619 0.00014854 -0.000205668 0.00010943 -0.000169186 0.000108129
465 -0.000865632 0.000144477 -0.000773993 0.000147544 -0.00075589 0.00014658 -0.000988087 0.000144413 -0.000156505 0.000105476 -8.25905e-05 0.000105574
495 -0.000629378 0.000141127 -0.000623762 0.000143276 -0.000515873 0.000141474 -0.000632128 0.000139918 6.58854e-05 0.000102925 0.000142795 0.000101104
525 -0.000381192 0.000137028 -0.000485868 0.000138853 -0.000488811 0.000137325 -0.000378744 0.000136093 -0.000178399 9.94419e-05 -0.000108842 9.83105e-05
555 -0.000316557 0.000134775 -0.000111786 0.000137465 7.7615e-07 0.000136395 -0.000426477 0.000136284 -9.9829e-05 9.84663e-05 -8.30525e-05 9.82943e-05
585 -0.000350289 0.000143513 0.000182359 0.000146112 -9.86412e-05 0.000144097 -0.000557966 0.000142452 -0.00011028 0.000104773 5.28255e-06 0.00010358
615 -0.000153503 0.000178495 -0.000316752 0.000182944 -8.82474e-05 0.000180418 -0.000122322 0.000179179 -0.000180061 0.000131985 -3.1576e-06 0.000131158
645 3.13415e-05 0.000289844 -0.000175759 0.00029405 -0.000132801 0.000293864 -0.000385774 0.000285481 -0.000105264 0.000210399 -0.000282981 0.0002095
675 -0.000961933 0.00061171 -0.00160522 0.000654816 -0.0014611 0.000676154 -0.000172568 0.000632494 -0.000732413 0.000461202 -0.000217323 0.000455566

Figure 4: macro, png, eps

cos(a-b) (Au+Au@200GeV)
centrality a+,b+,RFF stat err a+,b+,FF stat err a+,b+,RFF,rec stat err a+,b+,FF,rec stat err
0-5% -8.86702e-05 3.1494e-06 -2.05859e-05 3.04804e-06 -0.000168495 3.03309e-06 -0.000162705 2.85059e-06
5-10% -0.000119788 3.81749e-06 -7.18677e-05 3.66278e-06 -0.000181148 3.72233e-06 -0.000184491 3.50367e-06
10-20% -0.000155573 3.63068e-06 -0.000113014 3.45109e-06 -0.000201882 3.57819e-06 -0.000201566 3.35781e-06
20-30% -0.000194188 4.78392e-06 -0.000156577 4.53122e-06 -0.00022986 4.74422e-06 -0.00022444 4.46332e-06
30-40% -0.000225746 7.13899e-06 -0.000205466 6.73095e-06 -0.000256026 7.10758e-06 -0.000262823 6.67312e-06
40-50% -0.000307407 1.10278e-05 -0.000280297 1.03934e-05 -0.000335015 1.1001e-05 -0.000328381 1.03454e-05
50-60% -0.00037732 1.8344e-05 -0.000316498 1.73495e-05 -0.000403243 1.83161e-05 -0.000364104 1.72965e-05
60-70% -0.000412856 3.4088e-05 -0.000395875 3.21498e-05 -0.000444464 3.4053e-05 -0.000444511 3.21068e-05
70-80% -0.000395405 7.49043e-05 -0.000502187 7.06954e-05 -0.000443282 7.48502e-05 -0.000558773 7.06495e-05
centrality a-,b-,RFF stat err a-,b-,FF stat err a-,b-,RFF,rec stat err a-,b-,FF,rec stat err
0-5% -4.23982e-05 3.27251e-06 -7.23853e-05 3.04403e-06 -0.000164846 3.09367e-06 -0.000172573 2.90564e-06
5-10% -9.02915e-05 3.95928e-06 -0.000113398 3.69743e-06 -0.000186024 3.81234e-06 -0.00018816 3.58831e-06
10-20% -0.00013322 3.73725e-06 -0.000150212 3.50427e-06 -0.000207119 3.6521e-06 -0.00020764 3.44415e-06
20-30% -0.000169834 4.94047e-06 -0.000183032 4.6365e-06 -0.000226467 4.88231e-06 -0.000224549 4.59557e-06
30-40% -0.000223553 7.33453e-06 -0.000218098 6.90505e-06 -0.000270787 7.28437e-06 -0.000250925 6.87058e-06
40-50% -0.000281438 1.1311e-05 -0.00026869 1.06921e-05 -0.00032191 1.1268e-05 -0.000296577 1.06634e-05
50-60% -0.00031226 1.88279e-05 -0.000306347 1.77804e-05 -0.000350455 1.87885e-05 -0.000332508 1.77539e-05
60-70% -0.000367064 3.50004e-05 -0.00035379 3.30926e-05 -0.000410268 3.49581e-05 -0.000381376 3.3064e-05
70-80% -0.000293759 7.70607e-05 -0.000326476 7.28294e-05 -0.000352523 7.69997e-05 -0.000366779 7.27886e-05
centrality a+,b-,RFF stat err a+,b-,FF stat err a+,b-,RFF,rec stat err a+,b-,FF,rec stat err
0-5% 0.000424939 2.31175e-06 0.000443238 2.19887e-06 0.000346869 2.19632e-06 0.000345933 2.06688e-06
5-10% 0.000489124 2.7938e-06 0.000502678 2.65378e-06 0.000427985 2.69959e-06 0.000426757 2.5451e-06
10-20% 0.000589106 2.64708e-06 0.000606978 2.49965e-06 0.000540889 2.59415e-06 0.000546398 2.43789e-06
20-30% 0.000783002 3.48093e-06 0.000790412 3.28528e-06 0.000745594 3.44144e-06 0.000743832 3.24192e-06
30-40% 0.00105431 5.16729e-06 0.00106415 4.86426e-06 0.00102257 5.13271e-06 0.00102597 4.82798e-06
40-50% 0.0014258 7.90983e-06 0.00143299 7.47055e-06 0.00139831 7.88178e-06 0.00140117 7.43894e-06
50-60% 0.0019712 1.30566e-05 0.00198369 1.22975e-05 0.00194755 1.30298e-05 0.00195394 1.22702e-05
60-70% 0.0027773 2.39013e-05 0.00276417 2.25773e-05 0.00275386 2.387e-05 0.0027375 2.25468e-05
70-80% 0.00367447 5.03999e-05 0.0036616 4.75247e-05 0.00365069 5.03587e-05 0.00363606 4.74887e-05

Figure 5a: macro, png, eps

cos(a+b-2c), Au+Au@200GeV
centrality a+,b+,c:TPC stat err a+,b-,c:TPC stat err a+,b+,c:FTPC stat err a+,b-,c:FTPC stat err
0-5% -5.96721e-07 5.5117e-08 -2.55699e-07 5.5855e-08 -6.41226e-07 1.81669e-07 2.5831e-08 1.84138e-07
5-10% -1.64821e-06 8.10821e-08 -2.81993e-07 8.21354e-08 -1.13344e-06 2.21699e-07 -2.86037e-07 2.25777e-07
10-20% -4.09157e-06 9.52417e-08 -3.84498e-07 9.65213e-08 -2.60373e-06 2.18703e-07 -4.76965e-07 2.22735e-07
20-30% -8.60045e-06 1.54341e-07 -3.58936e-07 1.56032e-07 -5.79343e-06 3.10131e-07 -6.92628e-07 3.15673e-07
30-40% -1.49098e-05 2.71298e-07 -2.32776e-07 2.7367e-07 -9.55976e-06 4.98736e-07 -1.70223e-06 5.03745e-07
40-50% -2.27881e-05 4.88193e-07 1.25892e-06 4.88311e-07 -1.41551e-05 8.54669e-07 -3.76008e-07 8.54506e-07
50-60% -3.21049e-05 9.74197e-07 4.20594e-06 9.66534e-07 -2.08122e-05 1.65346e-06 3.58043e-07 1.64207e-06
60-70% -3.54594e-05 2.33159e-06 1.36972e-05 2.26937e-06 -1.64447e-05 3.84159e-06 6.90105e-06 3.75026e-06
70-80% -4.33681e-05 7.88093e-06 5.24459e-05 7.18626e-06 -2.70608e-05 1.23561e-05 2.88167e-05 1.15359e-05

Figure 5b: macro, png, eps

cos(a+b-2c)/v2c, Au+Au@200GeV
centrality a+,b+,c:TPC stat err a+,b-,c:TPC stat err a+,b+,c:FTPC stat err a+,b-,c:FTPC stat err
0-5% -2.72475e-05 2.51676e-06 -1.16758e-05 2.55046e-06 -6.41226e-05 1.81669e-05 2.5831e-06 1.84138e-05
5-10% -4.84767e-05 2.38477e-06 -8.2939e-06 2.41575e-06 -6.99655e-05 1.36851e-05 -1.76566e-05 1.39369e-05
10-20% -8.43622e-05 1.96375e-06 -7.9278e-06 1.99013e-06 -9.97598e-05 8.37942e-06 -1.82745e-05 8.53391e-06
20-30% -0.000139391 2.50148e-06 -5.81744e-06 2.52889e-06 -0.000163195 8.73608e-06 -1.95107e-05 8.89221e-06
30-40% -0.000212998 3.87569e-06 -3.32537e-06 3.90957e-06 -0.000232033 1.21052e-05 -4.13161e-05 1.22268e-05
40-50% -0.000310464 6.65112e-06 1.71515e-05 6.65273e-06 -0.000330728 1.99689e-05 -8.78524e-06 1.99651e-05
50-60% -0.000449019 1.36251e-05 5.88244e-05 1.3518e-05 -0.000503926 4.00354e-05 8.66932e-06 3.97595e-05
60-70% -0.000531625 3.49563e-05 0.000205355 3.40235e-05 -0.00046985 0.00010976 0.000197173 0.00010715
70-80% -0.000791388 0.000143813 0.000957043 0.000131136 -0.000800617 0.000365565 0.000852566 0.0003413

Figure 6: macro, png, eps

cos(a+b-2*psi_RP), @200GeV
centrality a+,b+,Au+Au stat err a+,b-,Au+Au stat err a+,b+,Cu+Cu stat err a+,b-,Cu+Cu stat err
0-5% -2.72475e-05 2.51676e-06 -1.16758e-05 2.55046e-06 -8.23628e-05 7.62553e-06 1.92707e-05 7.68691e-06
5-10% -4.84767e-05 2.38477e-06 -8.2939e-06 2.41575e-06 -0.000120783 8.77766e-06 2.76513e-05 8.82822e-06
10-20% -8.43622e-05 1.96375e-06 -7.9278e-06 1.99013e-06 -0.000170984 7.82902e-06 4.28017e-05 7.84248e-06
20-30% -0.000139391 2.50148e-06 -5.81744e-06 2.52889e-06 -0.000268721 1.08416e-05 9.16021e-05 1.08158e-05
30-40% -0.000212998 3.87569e-06 -3.32537e-06 3.90957e-06 -0.000360827 1.69498e-05 0.000133615 1.676e-05
40-50% -0.000310464 6.65112e-06 1.71515e-05 6.65273e-06 -0.000493512 2.87805e-05 0.00025283 2.82131e-05
50-60% -0.000449019 1.36251e-05 5.88244e-05 1.3518e-05 -0.000666972 5.33616e-05 0.000513905 5.13577e-05
60-70% -0.000531625 3.49563e-05 0.000205355 3.40235e-05        

Figure 7: macro, png, eps

cos(a+b-2*psi_RP), @62GeV
centrality a+,b+,Au+Au stat err a+,b-,Au+Au stat err a+,b+,Cu+Cu stat err a+,b-,Cu+Cu stat err
0-5% -4.23757e-05 9.80556e-06 -9.85927e-06 9.8707e-06 -0.000137923 1.99364e-05 -1.35041e-05 1.9788e-05
5-10% -7.40968e-05 1.3952e-05 -3.4003e-05 1.39647e-05 -0.000133313 2.11755e-05 4.62115e-05 2.09978e-05
10-20% -7.77459e-05 1.37515e-05 1.07891e-06 1.38198e-05 -0.000247374 2.00311e-05 6.3563e-05 1.97561e-05
20-30% -9.68171e-05 2.2324e-05 2.01104e-05 2.23629e-05 -0.000369201 2.80701e-05 4.95976e-05 2.75378e-05
30-40% -0.000265189 3.48369e-05 3.79756e-05 3.4502e-05 -0.000561217 4.33221e-05 8.12112e-05 4.2098e-05
40-50% -0.000293362 5.90266e-05 6.35767e-05 5.87266e-05 -0.000648074 8.48062e-05 0.000255673 8.08942e-05
50-60% -0.000699764 0.000112699 0.000119304 0.000109258 -0.000846257 0.000139251 0.000556567 0.000128056
60-70% -0.000612442 0.000169688 0.000259486 0.00015952        

Figure 8a: macro, png, eps

cos(a+b-2*psi_RP)*Npart @200GeV
centrality a+,b+,Au+Au stat err a+,b-,Au+Au stat err a+,b+,Cu+Cu stat err a+,b-,Cu+Cu stat err
0-5% -0.00959114 0.0008859 -0.00410986 0.000897761 -0.00905991 0.000838808 0.00211978 0.000845561
5-10% -0.0144461 0.000710661 -0.00247158 0.000719892 -0.0108705 0.000789989 0.00248861 0.00079454
10-20% -0.0197408 0.000459516 -0.00185511 0.00046569 -0.0126528 0.000579348 0.00316732 0.000580344
20-30% -0.023139 0.000415246 -0.000965695 0.000419796 -0.0145109 0.000585448 0.00494651 0.000584054
30-40% -0.0244947 0.000445705 -0.000382417 0.000449601 -0.0137114 0.000644092 0.00507738 0.00063688
40-50% -0.0235953 0.000505486 0.00130351 0.000505608 -0.0128313 0.000748294 0.00657358 0.000733541
50-60% -0.0206549 0.000626756 0.00270592 0.000621826 -0.0113385 0.000907147 0.00873639 0.000873081
60-70% -0.0138223 0.000908865 0.00533923 0.000884612        

Figure 8b: macro, png, eps

cos(a+b-2*psi_RP)*Npart @200GeV
Npart a+,b+,Au+Au stat err a+,b-,Au+Au stat err
352 -0.00959114 0.0008859 -0.00410986 0.000897761
298 -0.0144461 0.000710661 -0.00247158 0.000719892
234 -0.0197408 0.000459516 -0.00185511 0.00046569
166 -0.023139 0.000415246 -0.000965695 0.000419796
115 -0.0244947 0.000445705 -0.000382417 0.000449601
76 -0.0235953 0.000505486 0.00130351 0.000505608
46 -0.0206549 0.000626756 0.00270592 0.000621826
26 -0.0138223 0.000908865 0.00533923 0.000884612
Npart a+,b+,Cu+Cu stat err a+,b-,Cu+Cu stat err
111 -0.00905991 0.000838808 0.00211978 0.000845561
91 -0.0108705 0.000789989 0.00248861 0.00079454
75 -0.0126528 0.000579348 0.00316732 0.000580344
55 -0.0145109 0.000585448 0.00494651 0.000584054
39 -0.0137114 0.000644092 0.00507738 0.00063688
27 -0.0128313 0.000748294 0.00657358 0.000733541
18 -0.0113385 0.000907147 0.00873639 0.000873081

Figure 9a: macro, png, eps

cos(a+b-2*psi_RP) Au+Au@200GeV, centrality 30-50%
dEta a+,b+ stat err a+,b- stat err
0.1 -0.000368532 1.93889e-05 4.14406e-05 1.78412e-05
0.2 -0.000389154 1.98726e-05 -8.5758e-06 1.82828e-05
0.3 -0.000347259 2.04233e-05 -2.17184e-05 1.87871e-05
0.4 -0.000337929 2.10514e-05 -3.7387e-05 1.93519e-05
0.5 -0.000320795 2.17202e-05 -4.56147e-05 1.99689e-05
0.6 -0.000253858 2.25244e-05 -4.63337e-05 2.0705e-05
0.7 -0.000243289 2.34104e-05 -4.90444e-05 2.15174e-05
0.8 -0.000194821 2.44235e-05 -2.26662e-05 2.24388e-05
0.9 -0.000128307 2.55614e-05 9.82823e-06 2.34838e-05
1 -0.000139665 2.68826e-05 3.76055e-07 2.46838e-05
1.1 -0.000157202 2.84018e-05 -3.94043e-05 2.60877e-05
1.2 -9.82126e-05 3.02467e-05 -3.87571e-05 2.7755e-05
1.3 -0.00013351 3.24966e-05 -1.094e-05 2.98324e-05
1.4 -5.1006e-05 3.53599e-05 5.02523e-05 3.24443e-05
1.5 -8.56355e-05 3.91444e-05 -4.80189e-05 3.5939e-05
1.6 -7.14253e-06 4.41665e-05 6.23234e-05 4.05038e-05
1.7 -2.42515e-05 5.16733e-05 2.97413e-05 4.74294e-05
1.8 2.20165e-05 6.47772e-05 4.78176e-05 5.94367e-05
1.9 -3.14312e-05 9.57274e-05 0.000111678 8.77715e-05

Figure 9b: macro, png, eps

cos(a+b-2*psi_RP) Au+Au@200GeV, centrality 10-30%
dEta a+,b+ stat err a+,b- stat err
0.1 -0.000178186 7.71192e-06 9.75064e-07 7.05102e-06
0.2 -0.000181655 7.90414e-06 -2.75075e-05 7.22116e-06
0.3 -0.000158958 8.13093e-06 -2.05733e-05 7.43131e-06
0.4 -0.000149535 8.38016e-06 -1.5047e-05 7.65864e-06
0.5 -0.000120495 8.65929e-06 -2.38375e-05 7.91356e-06
0.6 -8.84987e-05 8.97813e-06 -1.28945e-05 8.2034e-06
0.7 -0.000100496 9.33385e-06 -1.49752e-05 8.52651e-06
0.8 -7.0445e-05 9.73617e-06 -1.47741e-05 8.89398e-06
0.9 -6.66536e-05 1.01883e-05 -1.02612e-05 9.30513e-06
1 -4.44654e-05 1.07066e-05 -8.59089e-06 9.7772e-06
1.1 -4.15335e-05 1.13052e-05 -1.29453e-05 1.03253e-05
1.2 -3.13472e-05 1.20279e-05 4.08344e-06 1.09822e-05
1.3 -2.383e-05 1.29182e-05 -3.67355e-06 1.1798e-05
1.4 7.14438e-07 1.40503e-05 3.31434e-05 1.28203e-05
1.5 -1.60998e-05 1.55438e-05 4.39071e-05 1.41923e-05
1.6 -1.30926e-05 1.75606e-05 4.84666e-06 1.60348e-05
1.7 2.35002e-05 2.06112e-05 3.67761e-05 1.88143e-05
1.8 2.13627e-05 2.59566e-05 -1.99469e-05 2.36932e-05
1.9 2.70098e-05 3.88126e-05 8.37627e-05 3.54448e-05

Figure 10a: macro, png, eps

cos(a+b-2*psi_RP) Au+Au@200GeV, centrality 30-50%
pt sum a+,b+ stat err a+,b- stat err
0.25 -1.86597e-05 4.82506e-05 0.000131891 4.19935e-05
0.35 -0.000168404 3.47549e-05 3.46201e-05 3.01673e-05
0.45 -0.000207891 3.34171e-05 2.86431e-05 2.89725e-05
0.55 -0.000310941 3.43469e-05 2.34082e-05 2.97232e-05
0.65 -0.000391535 3.63154e-05 -4.26482e-05 3.13792e-05
0.75 -0.000502117 3.98101e-05 -4.886e-05 3.43433e-05
0.85 -0.000540426 4.54117e-05 3.5897e-05 3.90816e-05
0.95 -0.000683329 5.34133e-05 -9.06207e-05 4.58721e-05
1.05 -0.000827452 6.39604e-05 -2.7063e-05 5.48576e-05
1.15 -0.000948429 7.73027e-05 -6.53509e-05 6.61969e-05
1.25 -0.00109269 9.37443e-05 -2.2286e-05 8.02133e-05
1.35 -0.00128669 0.000113811 -0.000143735 9.72948e-05
1.45 -0.00128052 0.000138324 -0.00029832 0.000118159
1.55 -0.00173005 0.00016816 -0.000110469 0.00014353
1.65 -0.00192021 0.000207982 -0.000200126 0.000177373
1.75 -0.00201955 0.000261336 0.000103889 0.000222654
1.85 -0.00216591 0.000331633 0.000207484 0.000282337
1.95 -0.00218459 0.000426053 -0.000256544 0.000362181
2.05 -0.00196731 0.000554984 0.000610387 0.00047096
2.15 -0.00223326 0.00073107 -0.0010659 0.000620133
2.25 -0.00276544 0.000976834 0.000875386 0.000827678

Figure 10b: macro, png, eps

cos(a+b-2*psi_RP) Au+Au@200GeV, centrality 10-30%
pt sum a+,b+ stat err a+,b- stat err
0.25 -2.06612e-05 2.0454e-05 5.156e-05 1.78039e-05
0.35 -8.44719e-05 1.42973e-05 1.92302e-05 1.24121e-05
0.45 -0.000122139 1.36589e-05 -1.68469e-05 1.18385e-05
0.55 -0.000129366 1.46395e-05 -5.0957e-06 1.26673e-05
0.65 -0.000179707 1.61996e-05 -8.05348e-06 1.40001e-05
0.75 -0.000238254 1.7952e-05 7.53611e-06 1.54954e-05
0.85 -0.000231923 2.0153e-05 -7.95715e-06 1.73638e-05
0.95 -0.000303857 2.33131e-05 -4.30243e-05 2.00503e-05
1.05 -0.00031866 2.79466e-05 -6.67366e-05 2.39755e-05
1.15 -0.00038018 3.43602e-05 -0.000100704 2.94024e-05
1.25 -0.000533262 4.27401e-05 -7.56699e-05 3.65306e-05
1.35 -0.000441765 5.32342e-05 -0.000109938 4.54565e-05
1.45 -0.000682588 6.60442e-05 -0.000144124 5.6375e-05
1.55 -0.000557763 8.14805e-05 -0.000259064 6.95221e-05
1.65 -0.000742154 0.000101524 -0.00010575 8.65791e-05
1.75 -0.000681588 0.000127306 -0.000104356 0.000108487
1.85 -0.000897995 0.000160127 -0.000137981 0.000136411
1.95 -0.00096773 0.000203044 -5.55571e-05 0.000172819
2.05 -0.000611806 0.000260404 8.24887e-05 0.000221367
2.15 -0.00145831 0.00033865 0.000465847 0.000287613
2.25 -0.00136431 0.000447146 0.000802626 0.000379469

Figure 11a: macro, png, eps

cos(a+b-2*psi_RP) Au+Au@200GeV, centrality 30-50%
delta pt a+,b+ stat err a+,b- stat err
0.15 -0.000570132 4.44496e-05 2.74526e-05 4.44756e-05
0.25 -0.000790017 4.6295e-05 -1.86276e-05 4.63183e-05
0.35 -0.000733443 4.8252e-05 -3.69426e-05 4.82585e-05
0.45 -0.000845225 5.03933e-05 -0.000176756 5.04128e-05
0.55 -0.000892947 5.28601e-05 -3.01604e-05 5.28608e-05
0.65 -0.000791999 5.57771e-05 -1.85454e-05 5.57635e-05
0.75 -0.000765128 5.92857e-05 -2.98023e-05 5.92656e-05
0.85 -0.000718002 6.34974e-05 -3.03018e-05 6.34702e-05
0.95 -0.000670958 6.85775e-05 -5.28269e-05 6.85097e-05
1.05 -0.000780415 7.46191e-05 -4.23097e-05 7.45444e-05
1.15 -0.000616988 8.17619e-05 -6.84859e-05 8.16977e-05
1.25 -0.000745754 9.01446e-05 3.4332e-05 9.00258e-05
1.35 -0.000695117 9.98154e-05 9.91924e-05 9.97415e-05
1.45 -0.000725004 0.000111012 1.29946e-05 0.000110838
1.55 -0.000800796 0.000123795 -0.000108198 0.000123587
1.65 -0.000862672 0.000138104 -0.000243131 0.00013794
1.75 -0.000597527 0.000154241 0.000225452 0.000154038
1.85 -0.000542748 0.000172125 7.15818e-05 0.000171969
1.95 -0.000841824 0.000192031 8.24761e-05 0.000191584
2.05 -0.000529912 0.000213962 -5.01992e-06 0.000213762
2.15 -0.00029975 0.000238872 -0.000244324 0.000238142
2.25 -0.000492216 0.000266899 -6.1186e-05 0.000266489
2.35 -0.00036984 0.000301408 0.000259713 0.000301192

Figure 11b: macro, png, eps

cos(a+b-2*psi_RP) Au+Au@200GeV, centrality 10-30%
delta pt a+,b+ stat err a+,b- stat err
0.25 -0.000381126 3.33924e-05 -4.03236e-05 3.3405e-05
0.35 -0.000432386 3.42273e-05 -5.67811e-05 3.42288e-05
0.45 -0.000400064 3.50049e-05 -3.30032e-05 3.50135e-05
0.55 -0.000432995 3.57841e-05 -0.000124951 3.57925e-05
0.65 -0.000469921 3.66111e-05 -7.5456e-05 3.66201e-05
0.75 -0.00045287 3.75741e-05 -0.000102602 3.7578e-05
0.85 -0.000428907 3.87401e-05 -5.18942e-05 3.8747e-05
0.95 -0.00037996 4.02101e-05 9.77211e-06 4.02184e-05
1.05 -0.000363232 4.2082e-05 -6.96972e-05 4.20963e-05
1.15 -0.000357043 4.44158e-05 -5.124e-05 4.44274e-05
1.25 -0.000339598 4.73103e-05 -8.84847e-05 4.73008e-05
1.35 -0.000416408 5.07762e-05 -6.66695e-05 5.07721e-05
1.45 -0.000341867 5.48549e-05 0.000109747 5.48451e-05
1.55 -0.000284264 5.95697e-05 -3.10067e-05 5.95747e-05
1.65 -0.000348883 6.48938e-05 7.08809e-05 6.49218e-05
1.75 -0.000355468 7.09345e-05 1.4693e-05 7.08864e-05
1.85 -0.00020167 7.75942e-05 -2.13547e-05 7.7614e-05
1.95 -0.000253686 8.50803e-05 5.45537e-05 8.50582e-05
2.05 -0.000465969 9.35876e-05 -0.000104112 9.35282e-05
2.15 -0.000405194 0.000103704 -9.74389e-05 0.000103674
2.25 -0.000332261 0.000116086 3.03482e-05 0.000115966
2.35 -0.000343455 0.000131657 -4.17877e-05 0.000131409

Figure 12: macro, png, eps

cos(a+b-2c)*Npart @200GeV
Npart a+,b+,Au+Au stat err a+,b-,Au+Au stat err
352 -0.000210046 1.94012e-05 -9.0006e-05 1.9661e-05
298 -0.000491166 2.41625e-05 -8.40338e-05 2.44763e-05
234 -0.000957427 2.22866e-05 -8.99726e-05 2.2586e-05
166 -0.00142767 2.56207e-05 -5.95834e-05 2.59014e-05
115 -0.00171463 3.11993e-05 -2.67692e-05 3.14721e-05
76 -0.00173189 3.71026e-05 9.56778e-05 3.71116e-05
46 -0.00147682 4.48131e-05 0.000193474 4.44606e-05
26 -0.000921945 6.06213e-05 0.000356127 5.90036e-05
Npart a+,b+,Cu+Cu stat err a+,b-,Cu+Cu stat err
111 -0.000279951 2.59192e-05 6.55011e-05 2.61278e-05
91 -0.000377206 2.74126e-05 8.63549e-05 2.75705e-05
75 -0.00052256 2.39271e-05 0.000130811 2.39682e-05
55 -0.000689268 2.78088e-05 0.000234959 2.77426e-05
39 -0.000706138 3.31708e-05 0.000261485 3.27993e-05
27 -0.000667229 3.89113e-05 0.000341826 3.81441e-05
18 -0.000586202 4.68995e-05 0.000451671 4.51383e-05

Figure 13: macro, png, eps

cos(a+b-2*psi_RP) Au+Au@200GeV
centrality a+,b+ stat err a+,b- stat err
5-10% -4.84767e-05 2.38477e-06 -8.2939e-06 2.41575e-06
10-20% -8.43622e-05 1.96375e-06 -7.9278e-06 1.99013e-06
20-30% -0.000139391 2.50148e-06 -5.81744e-06 2.52889e-06
30-40% -0.000212998 3.87569e-06 -3.32537e-06 3.90957e-06
40-50% -0.000310464 6.65112e-06 1.71515e-05 6.65273e-06
50-60% -0.000449019 1.36251e-05 5.88244e-05 1.3518e-05
60-70% -0.000531625 4.49563e-05 0.000205355 4.40235e-05

Monte-Carlo number for Fig. 13

HIJING
centrality a+,b+ stat err a+,b- stat err
30-40% -9.93524e-06 4.2788e-06 -6.64e-06 4.74e-06
60-70% 2.135e-05 2.89914e-05 -6.8e-05 2.6e-05
HIJING+v2
centrality a+,b+ stat err a+,b- stat err
30-40% -7.10673e-07 3.92277e-06 7.76878e-06 2.75007e-06
40-50% -1.39227e-06 5.87389e-06 1.30744e-05 4.1165e-06
50-60% -9.2582e-06 9.33568e-06 1.47317e-05 6.51374e-06
60-70% -4.21107e-05 1.64567e-05 2.50399e-05 1.13663e-05
UrQMD
centrality a+,b+ stat err a+,b- stat err
12% -6.33629e-06 6.85204e-06 -1.849e-05 7.41e-06
40% -6.25453e-05 9.0154e-06 -6.4e-05 9e-06
69% -0.000113128 3.42632e-05 -0.000215 3.79e-05
MEVSIM
centrality a+,b+ stat err a+,b- stat err
40-50% 1.17707e-05 1.05347e-05 9.5e-05 1.2e-05
HIJING 3-particle background: cos(a+b-2c)/v2[data]
centrality a+,b+ a+,b-
5-10% 1.59273e-06 4.24727e-06
10-20% 1.74886e-06 4.66362e-06
20-30% 2.61747e-06 6.97991e-06
30-40% 4.84958e-06 1.29322e-05
40-50% 1.05797e-05 2.82126e-05
50-60% 2.82856e-05 7.54282e-05
60-70% 9.30982e-05 0.000248262

W 2009 analysis


Plot from DNP2009 presentation

STAR W 2009 analysis


Paper proposals

  1. W+/W- longitudinal single-spin asymmetry

    Title: Measurement of the parity-violating longitudinal single-spin asymmetry
    for W+/W- boson production in polarized p+p collisions at √s=500GeV

    Journal: Physical Review Letters

  2. W-/W+ boson production cross sections

    Title: Measurement of the W-/W+ boson production cross sections
    at mid-rapidity in p+p collisions at √s=500GeV at RHIC

    Journal: Physical Review D

Principal authors

Peripheral Collisions

Ultra Peripheral Collisions

Fast moving highly-charged ions carry strong electromagnetic fields that act as a beam of photons. In collisions at large impact parameters (b>R1+R2), hadronic interactions are not possible, and the ions interact through photon-ion and photon-photon collisions known as ultra-peripheral collisions (UPCs).  Ultra-peripheral hadron-hadron collisions will provide unique opportunities for studying electromagnetic processes. Ultra-relativistic heavy-ion interactions have been used to study nuclear photo excitation (e.g., to a Giant Dipole Resonance) and photoproduction of hadrons.

 

                                                                                                  

Hadron colliders like the Relativistic Heavy Ion Collider (RHIC), the Tevatron, and the Large Hadron Collider (LHC) produce photonuclear and two-photon interactions at luminosities and energies beyond that accessible elsewhere.

 

 

Introduction

Fast moving highly-charged ions carry strong electromagnetic fields that act as a beam of photons. In collisions at large impact parameters, hadronic interactions are not possible, and the ions interact through photon-ion and photon-photon collisions known as ultra-peripheral collisions (UPCs).  Ultra-peripheral hadron-hadron collisions will provide unique opportunities for studying electromagnetic processes. Ultra-relativistic heavy-ion interactions have been used to study nuclear photo excitation (e.g., to a Giant Dipole Resonance) and photoproduction of hadrons.

Hadron colliders like the Relativistic Heavy Ion Collider (RHIC), the Tevatron, and the Large Hadron Collider (LHC) produce photonuclear and two-photon interactions at luminosities and energies beyond that accessible elsewhere.

 

 

Physics Analysis 2016

Coherent diffractive photoproduction of rho mesons on gold nuclei at RHIC

Target Journal: Physics Letters B

PAs: Ramiro Debbe, Spencer Klein

PWG presentation: STAR/system/files/userfiles/2729/file/RhoCoherentDiffractionV6.pdf

Abstract:

 

The STAR Collaboration reports on the photoproduction of π+πpairs in gold-gold collisions at a center of mass energy of 200 GeV/nucleon. These pairs are produced when a nearly-real photon emitted by one ion scatters from the other ion. We fit the π+πmass spectrum to a combination of ρ0 and ω resonances and a direct π+πcontinuum; the ratio of ρ0 to direct π+πis consistent with previous measurements. The ω cross-section is comparable with that expected from the measured γp ωp cross section, a classical Glauber calculation and the ω π+πbranching ratio.

The ρ0 differential cross section dσ/dt clearly exhibits a diffraction pattern, compatible with scattering from a gold nucleus, with 2 minima visible.


Figures:

Figure 1: The black histogram shows the pion pair transverse momentum. The peak below 100 MeV/c is from the decay of coherently produced π+πpairs. The red histogram shows the pair momentum for same-sign pion pairs. Both histograms show pairs that come from vertices with only two tracks.

Figure 2: Comparison of uncorrected data (blue points) with embedded simulated ρ0 and direct ππ events (yellow histogram). The simulated UPCs were run through a GEANT sim- ulation of the detector, embedded in zero-bias background events, and subject to the same reconstruction programs as the data.

Figure 3: The shower energy in the West ZDC by neutron produced by mutual dissociation is shown as a distribution of ADC channels. These events had a single neutron detected on the East ZDC. The peaks corresponding to 1 to 4 neutrons are fitted with Gaussian distributions with standard deviations that grow as with n the number of neutrons and σ the standard deviation of the one neutron Gaussian. The red curve is the sum of all Gaussians which are also displayed individually. The quality of fit is χ2/NDF = 498/88. The large χ2/NDF is due to the very small statistical errors and the imperfect descriptions of the neutron peaks. It does not introduce significant errors on the number of neutrons in each peak.

Figure 4: The π+πinvariant-mass distribution for all selected ππ candidates with pT < 100 MeV/c. The black markers show the data (in 2.5 MeV/c2 bins). The black curve is the modified S ̈oding fit to the data in the range 0.53 < Mππ < 1.3 GeV. The ρ0 Breit-Wigner component of the fitted function is shown with a blue curve and the constant non-resonant pion pair component is displayed with a black-dashed one. The interference between non- resonant pion pairs and the ρ0 meson is shown with a blue-dashed curve. The Breit-Wigner distribution for the ω mesons is shown with a red curve and the interference between ρ0 and ω is shown with a red-dashed curve. A small second order polynomial shown with a cyan-dashed curve accounts for the remnant background.

Figure 5: (Top) The ratio |B/A| of amplitudes of non-resonant π+πand ρ0 mesons. The black points (with shaded blue systematic error band) are from the current analysis, while the previous STAR results are shown with blue-filled circles. The thick black line shows the rapidity-averaged result. In the bottom panel, the black points show the ratio |C/A| of the ω to ρ0 amplitude. The red band shows the systematic errors, while the horizontal blue line shows the STARlight prediction and the most recent branching ratio for ω π+πdecay [26]. The green band shows the DESY-MIT result for |C/A| [27]. This result was at much lower photon energies leads to a large effective rapidity. For the lower energy photon solution of the two-fold ambiguity, the effective rapidity would be about 2.5.

Figure 6: dσ/dy for exclusively photoproduced ρ0 mesons in (top) XnXn events and (bottom) 1n1n events. The data are shown with red markers. The statistical errors are smaller than the symbols, the orange band shows the quadrature sum of the point-to-point systematic uncertainties. The red box at y ∼ −0.9 shows the quadrature sum of the common systematic uncertainties. The black histograms are the STARlight calculation for ρ0 mesons with mutual dissociation. The blue markers in the top panel show the previous STAR measurement [10].

Figure 7: The t distribution for exclusive ρ0 mesons in events with 1n,1n mutual dissociation (blue markers) or XnXn (red markers). The high t part of those distributions, which is dominated by the contribution from incoherent interactions is fit to a dipole form factor, shown with a thin line. The STARlight prediction for the incoherent contribution is shown by the histogram with small black markers.

Figure 8: Fully normalized coherent diffraction patterns for ρ0 mesons detected in exclusive XnXn events is shown with red markers. The same distribution but extracted from 1n1n events is shown with black markers. The filled bands shows the sum in quadrature of all systematic uncertainties listed in table 4 and the statistical errors, which are shown as vertical lines.The insert shows, with finer binning at low pT , the effects of the destructive interference between photoproduction with the photon emitted by any of the two ions.

Figure 9: The normalized nucleon distribution in the transverse plane, the result of a two- dimensional Fourier transform (Hankel transform) of the XnXn and 1n1n diffraction patterns shown in Fig. 8. The integration is limited to a region where data is available; in the range 0 < |t| < 0.06 GeV2. The cyan error band shows the effect of changing the maximum t to 0.05, 0.07 and 0.09 GeV2. In order to highlight the similarity of both results at their falling edges, the resulting histograms are scaled by their integrals from -12 to 12 fm. The FWHM of both transforms is 2 × (6.17 ± 0.12) fm consistent with the coherent diffraction of ρ0 mesons off an object as big as the Au nuclei.

Paper conclusions:

In conclusion, STAR has made a precision study of ρ, ω and direct π+πphotoproduction in 200 GeV/nucleon gold-on-gold ultra-peripheral collisions, using 394,000 π+πpairs.

We fit the invariant mass spectrum to a mixture of ρ, ω and direct π+π(including interference terms). The ratio of ρ to direct ππ is similar to that in previous measurements, while the newly measured ω contribution is comparable with predictions based on on the previously measured γp ωp cross section and the ω π+πbranching ratio. The relative fractions of ρ, ω and direct π+πdo not vary significantly with rapidity, indicating that they all have a similar dependence on photon energy.

We also measure the cross section dσ/dt over a wide range, and separate out coherent and incoherent components. The coherent contribution exhibits

multiple diffractive minima, indicating that the nucleus is beginning to act like a black disk.


Analysis note (STAR Note psn0650)
The current version of the note can be found at: STAR/system/files/userfiles/2729/file/Main_analysisNote_RhoDiffraction.pdf
Section 9.7 has detailed instructions on how to reproduce the UPC pico-dst used in this analysis and the macros used to generate the figures of the paper.
The code for this analysis is stored in STAR CVS, to retrieve it do:

cvs co offline/paper/psn0650

Paper drafts:

First_draft     - First circulation to UPC PWG

Second_draft - request for a GPC

Third_draft   - first GPC revision

Fourth_draft   - Oct. 24, 2016 - version for collaboration review

Final Draft - Feb 7, 2017.  This is the final version, after collaboration review and GPC approval.   It includes the current author list and acknowledgements, as of Feb. 7th.    Also attached are detailed responses to the collaboration comments, in a single document.

Final, Final draft., Feb. 20th, 2017.    This is the version after including comments from Norbert Schmitz.  The response to Norbert is here.

May 10, 2017. The Physics Letters B Referee Report is here.

May 10, 2017. After discussion with the GPC, we decided to sent it to Physical Review C., with a very few changes in response to the PLB referee reports.  The Physical Review C version is here.

September 26, 2017.  After four months, PRC sent us a positive referee report, which is attached here.   Our proposed response is attached here,  and the revised manuscript is attached here.

UPC Talks

Dilan's Talks

STARlight

 STARlight is a Monte Carlo that simulates two-photon and photon-Pomeron interactions between relativistic nuclei and protons. More information can be found here.

Contact Us

1. Dilan Madagodahettige Don (Creighton University)  Email: dilan@creighton.edu

Images

Spin

STAR Spin Working Group 

 

 

Unraveling the quark and gluon substructure of nucleons and nuclei is one of the major goals in nuclear physics today. A great deal has been learned about the partonic structure of the nucleon at leading twist and with collinear factorization, but much is still unknown. Furthermore, new avenues have been opened during the past decade to explore the nucleon structure beyond leading twist and collinear factorization. The ability to collide polarized beams at RHIC provides unique information regarding these issues.

                                 - STAR Decadal Plan (2010)

Spin PWG

Spin Physics Working Group pages

This is a feed of Drupal items targeting the "Spin" Audience.

Physics Analysis

Detailed information about physics analyses in the spin pwg

Link to STAR spin task force (2008)

(page started in March of 2008)

2006 EEMC Neutral Pion Cross Section and A_LL

The 2006 EEMC cross section, ALL, and AN were published in Physical Review D 89, 012001 (2014). Please, see the paper home page for links to detailed information.

Relevant Links

2006 Gamma + Jet

Relevant Links

Intent to Publish 2006 Gamma + Jet Cross Section

Title

Gamma-jet cross sections for forward gammas in proton-proton collisions at root(s) = 200 GeV/c

Principal Authors (alphabetical order)

Keith Krueger (ANL), Hal Spinka (ANL), Dave Underwood (ANL)

Intended Journal

Physical Review D

Abstract

A measurement is presented of the cross section vs. transverse momentum (pT) for gamma + jet production in proton-proton collisions. The data were measured in the STAR detector at RHIC at √s = 200 GeV/c. The jet was detected at central pseudorapidity (|η| < 0.8) and the γ at intermediate pseudorapidity (1.2 < η < 2.0). These regions were chosen to access lower x of the gluon relative to a central-pseudorapidity-only measurement, and also because a large partonic spin asymmetry, All, in the parton cm is selected. The technique of finding single γ’s in the background of photons from π0 decay is based on a standard chi-squared method for the shower shape in the shower maximum detector of an electromagnetic calorimeter.

Outline

  • Introduction
    • Refs. to earlier measurements and theory predictions
    • Connection to gluon distribution
  • Hardware
    • RHIC general (Refs.)
    • STAR general (Refs.)
    • TPC and BEMC for jets (Refs.)
    • EEMC and ESMD for gamma
    • trigger
    • luminosity
  • Analysis
    • Jets (Refs.)
    • Gammas with chi-squared (Ref.)
    • Efficiency / RooUnfold
    • Other Corrections?
    • Systematics
    • Table of results with errors
  • Results
    • Comparison to JETPHOX (Refs.)
    • Comparison to pi0’s?
  • Summary / Conclusions

Presentations to the Spin PWG (April 23)

2009 Lambda D_LL @ 200 GeV



Presentations: 



Run QA by Qinghua Xu (SDU) 
 

1) Preliminary results

Preliminary released on SPIN 2012 and DNP 2012. 

Presentation @ SPIN 2012 by Jian Deng (SDU)
Presentation @ DNP 2012 by Ramon Cendejas (UCLA)

2) Lambda reconstruction

 

1. Cuts setup:
lam_pt dac2 dcaV0 dca_p dca_pi nsigma dlength cosrp jet_det_eta jet_Rt jet_dr
2,3 <0.7 <1.2 >0.2 (0.4,30) <3 (3,130) >0.98 (-0.7,0.7) (0.01,0.94) <0.7
3,4 <0.5 <1.2 0 (0.4,30) <3 (3.5,130) >0.98 (-0.7,0.7) (0.01,0.94) <0.7
4,5 <0.5 <1.2 0 (0.4,30) <3 (4,130) >0.98 (-0.7,0.7) (0.01,0.94) <0.7
5,8 <0.5 <1.2 0 (0.4,30) <3 (4.5,130) >0.98 (-0.7,0.7) (0.01,0.94) <0.7


2. Analysis plots: 

cos\theta^* vs mass by pT .pdf 
slope band from K0-short: .pdf 


3. Invariant Mass distribution and background estimation, side band vs. fitting 


All 4 lambda pT bins, fired jet only .pdf .txt no fired jet required .pdf .txt  

4. Extract Lambda and Anti-Lambda yields for 20 cos \theta^* , for 4 spin status, for JP1 and L2JetHigh triggers. 
Lambda pT Lambda JP1 AntiLambda JP1 Lambda L2JetHigh AntiLambda L2JetHigh
2, 3 FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html
3, 4 FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html
4, 5 FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html
5, 8 FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html
 

5. Extract DLL from the spin sorted Lambda/AntiLambda yeilds in each cos \theta^* bin, for each trigger
Lambda pT Lambda JP1 AntiLambda JP1 Lambda L2JetHigh AntiLambda L2JetHigh
2, 3 FiredJet .html  noFire .html FiredJet .html  noFire .html FiredJet .html  noFire .html FiredJet .html  noFire .html
3, 4 FiredJet .html  noFire .html FiredJet .html  noFire .html FiredJet .html  noFire .html FiredJet .html  noFire .html
4, 5 FiredJet .html  noFire .html FiredJet .html  noFire .html FiredJet .html  noFire .html FiredJet .html  noFire .html
5, 8 FiredJet .html  noFire .html FiredJet .html  noFire .html FiredJet .html  noFire .html FiredJet .html  noFire .html


6. Fit DLL vs. cos \theta^* to extract the "DLL"


Lambda pT Lambda JP1 AntiLambda JP1 Lambda L2JetHigh AntiLambda L2JetHigh
2, 3 FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html
3, 4 FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html
4, 5 FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html
5, 8 FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html FiredJet.pdf .txt .html  noFire .pdf .txt .html


7. DLL correction 


Appendix,  Anti-Lambda/Lambda ratio: 


3) New simulation production

Background 
Simulations performed by Ramon Cendejas. Unfortunately, an error was found in the (subdominant) process contributions when Ramon needed to move on. This and other factors held up progress since.


Introduction
  • Pure MC simulation under STAR geometry.
  • Generate pp events using Pythia 6.4.28 (Tune 320) with Lambda filter, in different partonic pT intervals and weighted by integral luminosities
  • Reconstruct Lambda based on track association
  • Jet reconstruction used CDF cone algorithm with R = 0.7


Statistics of simulation sample 
It totally took about 4.5 CPU years. 


  
Slides20170110  

Jet Cone Study 
1. slides (JP1 lambda pt2-3 for example)    
2. All comparison plots for different lambda pt bin and different Triggers 

Trigger Bias Plot 
1. updated version for cdf cone algorigthm

Data/MC comparison for
Lambda: 

lamdba pt JP1 L2JetHigh
2_3 file file
3_4 file file
4_5 file file
5_8 file file
Anti-lambda: 
A-lamdba pt JP1 L2JetHigh
2_3 file file
3_4 file file
4_5 file file
5_8 file file

QA: 
lamdba pt MB JP1 L2JetHigh
2_3 file file file
3_4 file file file
4_5 file file file
5_8 file file file

Trigger effect: (old, anti-kt R06 )
  f_z feed down parton subprocess
Lambda file1 file2 file file file
A-lambda file1 file2 file file file





 

4) Systematic uncertainties

Systematic uncertainties summary

  • decay, fz, and f_parton from simulation 
  • pile-up and residual background are from preliminary version

    η > 0   η < 0
    Lambda Anti-lambda   Lambda Anti-lambda
  pt JP1 L2J JP1 L2J   JP1 L2J JP1 L2J
decay 2.4 0.0009 0.0018 0.0001 0.0003   0.0001 0 0.0001 0.0001
3.4 0.0008 0.0011 0.0004 0.0003   0 0.0001 0 0
4.4 0.002 0.0027 0.0008 0.0008   0.0003 0.0004 0.0001 0.0002
5.9 0.0017 0.0024 0.0013 0.0022   0.0005 0.0009 0.0003 0.0007
                     
fz 2.4 0.0011 0.0028 0.0003 0.0015   0.0002 0.0001 0.0001 0.0001
3.4 0.001 0.0034 0.0006 0.0024   0.0003 0.0005 0.0003 0
4.4 0.0056 0.008 0.0053 0.0079   0.0005 0.0007 0.0009 0.0013
5.9 0.009 0.0121 0.0154 0.0191   0.0021 0.0028 0.0037 0.0046
                     
fparton 2.4 0.0005 0.0008 0.0004 0.0012   0.0001 0.0001 0.0001 0.0002
3.4 0.0011 0.0021 0.0002 0.0013   0.0003 0.0005 0 0.0003
4.4 0.0019 0.0038 0.0003 0.0011   0.0005 0.0009 0.0001 0.0003
5.9 0.0034 0.0062 0.0016 0.0027   0.0011 0.002 0.0005 0.0009
                     
pile-up 2.4 0.0182 0.0057 0.0184 0.0063   0.0182 0.0057 0.0184 0.0063
3.4 0.0023 0.0007 0.0022 0.001   0.0023 0.0007 0.0022 0.001
4.4 0.0023 0.0007 0.0022 0.001   0.0023 0.0007 0.0022 0.001
5.9 0.0068 0.0023 0.0064 0.0023   0.0068 0.0023 0.0064 0.0023
                     
bkgd 2.4 0.005 0.001 0.0001 0.0002   0.005 0.001 0.0001 0.0002
3.4 1.00E-06 0.0001 0.0001 0.0006   1.00E-06 0.0001 0.0001 0.0006
4.4 0.0007 4.00E-05 0.0004 0.0002   0.0007 4.00E-05 0.0004 0.0002
5.9 0.0002 0.0002 0.001 0.0001   0.0002 0.0002 0.001 0.0001
                     
all 2.4 0.0189 0.0067 0.0184 0.0066   0.0189 0.0058 0.0184 0.0063
3.4 0.0029 0.0042 0.0023 0.0030   0.0023 0.0010 0.0022 0.0012
4.4 0.0067 0.0093 0.0058 0.0081   0.0025 0.0014 0.0024 0.0017
5.9 0.0119 0.0140 0.0168 0.0196   0.0072 0.0042 0.0075 0.0053



2009 dijet x-sect/A_LL @ 200 GeV

 

2011 FMS Jet-like correlations @ 500 GeV

 

2011 FMS inclusive pions @ 500 GeV

 

2012 Jet A_LL @ 500 GeV

 

2012 Lambda D_TT @200GeV

 

1) Dataset and RunQA

Dataset for pp200trans_2012 D_TT analysis


Statistics Summary

Dataset: pp200trans_2012

Integrated Luminosity: 18.4 pb^-1

Selected Triggers: JP0, JP1, JP2, AJP

Event Statistics For Each Trigger:

Trigger JP0 JP1 JP2 AJP Combined
HardXSoft 2.461964e+07 8.525444e+07 1.797188e+07 1.391969e+07 1.417656e+08

Data QA

 

2) Lambda Reconstruction

The reconstruction of Lambda and anti-Lambda hyperons.

Identification cut on track’s dE/dx measured in TPC is used to find pion and (anti-)proton.

Sketch for Topological Cuts 



Values:

  a) Statistics of Lambda and anti-Lambda Reconstruction, Inclusive
  b) Statistics of Lambda and anti-Lambda Reconstruction, Jet near-side

  Only the jet near-side Lambda used to extract D_TT.

The comparison about the reconstruction status with two sets of cut are shown here.
The loose one is the cut set used in run09 D_LL analysis and the tight one.

a) Statistics of Lambda and anti-Lambda Reconstruction, Inclusive

D_TT analysis Record, Rec_Step: all_cut_crp0995

Invariant Mass

Statistics Summary

====> Lambda

 
JP0
 
 
 
JP1
 
 
 
JP2
 
 
 
AJP
 
 
 
Combined
 
 
 
pt_T [GeV/c]
Central [GeV]
Width [GeV]
N_candidate
bkg fraction
Central [GeV]
Width [GeV]
N_candidate
bkg fraction
Central [GeV]
Width [GeV]
N_candidate
bkg fraction
Central [GeV]
Width [GeV]
N_candidate
bkg fraction
Central [GeV]
Width [GeV]
N_candidate
bkg fraction
1~2 1.1154 0.0016 364262 0.0536 1.1155 0.0016 1394859 0.0570 1.1155 0.0016 280707 0.0666 1.1155 0.0016 338322 0.0546 1.1155 0.0016 2378150 0.0572
2~3 1.1157 0.0021 96583 0.0609 1.1157 0.0021 496180 0.0654 1.1157 0.0022 122363 0.0758 1.1157 0.0021 118569 0.0631 1.1157 0.0021 833695 0.0660
3~4 1.1158 0.0027 25879 0.0612 1.1158 0.0028 186321 0.0649 1.1158 0.0028 57674 0.0748 1.1158 0.0027 38191 0.0609 1.1158 0.0028 308065 0.0659
4~5 1.1161 0.0035 6360 0.0616 1.1160 0.0034 65638 0.0644 1.1159 0.0034 25367 0.0703 1.1160 0.0035 11204 0.0565 1.1160 0.0034 108569 0.0648
5~6 1.1162 0.0041 1782 0.0791 1.1162 0.0042 25415 0.0720 1.1162 0.0042 11736 0.0745 1.1163 0.0042 3484 0.0669 1.1162 0.0042 42417 0.0726
6~8 1.1168 0.0051 729 0.0938 1.1166 0.0051 14932 0.0884 1.1166 0.0052 8622 0.0912 1.1169 0.0051 1853 0.0835 1.1166 0.0051 26136 0.0891

====> anti-Lambda

 
JP0
 
 
 
JP1
 
 
 
JP2
 
 
 
AJP
 
 
 
Combined
 
 
 
pt_T [GeV/c]
Central [GeV]
Width [GeV]
N_candidate
bkg fraction
Central [GeV]
Width [GeV]
N_candidate
bkg fraction
Central [GeV]
Width [GeV]
N_candidate
bkg fraction
Central [GeV]
Width [GeV]
N_candidate
bkg fraction
Central [GeV]
Width [GeV]
N_candidate
bkg fraction
1~2 1.1155 0.0015 299136 0.0755 1.1155 0.0016 1048977 0.0834 1.1155 0.0015 195241 0.0999 1.1155 0.0015 284645 0.0735 1.1155 0.0017 1827999 0.0823
2~3 1.1157 0.0020 102267 0.0676 1.1157 0.0020 468030 0.0743 1.1157 0.0021 97877 0.0931 1.1157 0.0020 114900 0.0702 1.1157 0.0020 783074 0.0751
3~4 1.1159 0.0026 26961 0.0663 1.1159 0.0026 183094 0.0680 1.1158 0.0027 46292 0.0860 1.1159 0.0027 34646 0.0694 1.1159 0.0027 290993 0.0709
4~5 1.1162 0.0033 5659 0.0660 1.1161 0.0034 61114 0.0635 1.1160 0.0034 19641 0.0741 1.1161 0.0035 8582 0.0678 1.1161 0.0034 94996 0.0662
5~6 1.1166 0.0043 1301 0.0707 1.1163 0.0041 20461 0.0756 1.1162 0.0041 8679 0.0798 1.1164 0.0041 2292 0.0794 1.1163 0.0041 32733 0.0768
6~8 1.1168 0.0057 459 0.1046 1.1168 0.0053 10175 0.1061 1.1166 0.0051 5581 0.1092 1.1172 0.0053 972 0.1086 1.1168 0.0052 17187 0.1072

Lambda candidates invariant mass distributions for each p_T range

Trigger: JP0 Distribution Statistics

Trigger: JP1 Distribution Statistics

Trigger: JP2 Distribution Statistics

Trigger: AJP Distribution Statistics

Trigger: Combined Distribution Statistics

ant-Lambda candidates invariant mass distributions for each p_T range

Trigger: JP0 Distribution Statistics

Trigger: JP1 Distribution Statistics

Trigger: JP2 Distribution Statistics

Trigger: AJP Distribution Statistics

Trigger: Combined Distribution Statistics

Distributions for p_T, eta, phi

Lambda candidates p_T, eta, phi distributions for each p_T range

Trigger: JP0 pT eta phi

Trigger: JP1 pT eta phi

Trigger: JP2 pT eta phi

Trigger: AJP pT eta phi

Trigger: Combined pT eta phi

anti-Lambda candidates p_T, eta, phi distributions for each p_T range

Trigger: JP0 pT eta phi

Trigger: JP1 pT eta phi

Trigger: JP2 pT eta phi

Trigger: AJP pT eta phi

Trigger: Combined pT eta phi

Distributions of variables used as topolagical cuts

Lambda candidates decay length, dca2, dcaV0 and cosrp distributions for each p_T range

Trigger: JP0 decay length dca2 dcaV0 cosrp

Trigger: JP1 decay length dca2 dcaV0 cosrp

Trigger: JP2 decay length dca2 dcaV0 cosrp

Trigger: AJP decay length dca2 dcaV0 cosrp

Trigger: Combined decay length dca2 dcaV0 cosrp

anti-Lambda candidates decay length, dca2, dcaV0 and cosrp distributions for each p_T range

Trigger: JP0 decay length dca2 dcaV0 cosrp

Trigger: JP1 decay length dca2 dcaV0 cosrp

Trigger: JP2 decay length dca2 dcaV0 cosrp

Trigger: AJP decay length dca2 dcaV0 cosrp

Trigger: Combined decay length dca2 dcaV0 cosrp

Distributions of variables of daughter particles

dca of daughters is also used as cut

Proton from Lambda candidates: p_T, eta, phi and dca distributions for each p_T range

Trigger: JP0 p_T eta phi dca

Trigger: JP1 p_T eta phi dca

Trigger: JP2 p_T eta phi dca

Trigger: AJP p_T eta phi dca

Trigger: Combined p_T eta phi dca

Pion from Lambda candidates: p_T, eta, phi and dca distributions for each p_T range

Trigger: JP0 p_T eta phi dca

Trigger: JP1 p_T eta phi dca

Trigger: JP2 p_T eta phi dca

Trigger: AJP p_T eta phi dca

Trigger: Combined p_T eta phi dca

Proton from anti-Lambda candidates: p_T, eta, phi and dca distributions for each p_T range

Trigger: JP0 p_T eta phi dca

Trigger: JP1 p_T eta phi dca

Trigger: JP2 p_T eta phi dca

Trigger: AJP p_T eta phi dca

Trigger: Combined p_T eta phi dca

Pion from anti-Lambda candidates: p_T, eta, phi and dca distributions for each p_T range

Trigger: JP0 p_T eta phi dca

Trigger: JP1 p_T eta phi dca

Trigger: JP2 p_T eta phi dca

Trigger: AJP p_T eta phi dca

Trigger: Combined p_T eta phi dca

3) Extraction of D_TT

D_TT extraction Procedure Plots    

 

5) Trigger Bias Study

MC samples before and after trigger conditions applying are used for trigger bias study.

  • changes in the fractional momentum z of the produced Lambda and anti-Lambda
 within the associated jet,
    changes in the relative contributions from different hard sub-processes and fragmenting partons with different flavors in the production.
    possible differences in the fraction of feed-down contributions.

Please maximize your web browser before open the following links or some plots may not show up.

1, Trigger bias parameters plots 

2, Uncertainty to D_TT from trigger bias



6) Paper proposal

Title:

Transverse spin transfer of Lambda and Anti-Lambda Hyperons in Polarized proton-proton collisonns at \sqrt{s}=200 GeV at RHIC

PAs:  Jincheng Mei,Qinghua Xu

Proposed Target Journal: Phys. Rev. D

Abstract:
The transverse spin transfer from polarized protons to Λ and Λ̄ hyperons is expected to provide sensitivity to the transversity distribution of the nucleon and to the transversely polarized fragmen- tation functions. We report the first measurement of the transverse spin transfer to Λ and Λ̄ along the polarization direction of the fragmenting quark, D_TT, in transversely polarized proton-proton collisions at sqrt{s} = 200 GeV with the STAR detector at RHIC. The data correspond to an integrated luminosity of 18 pband cover the pseudorapidity range |η| < 1.2 and transverse momenta p_up to8 GeV/c. The dependence on p_and η are presented. The D_TT results are found to be comparable with a model prediction, and are also consistent with zero within uncertainties.


Figures: 

FIG. 1: The invariant mass distribution for Lambda (open circles) and anti-Lambda (filled circles) candidates for trigger combined sample after selections with 1 <$p_{\mathrm{T}}$ < 8 GeV/c in this analysis. 



FIG. 2:
The invariant mass distribution versus cos\theta^{*} for Lambda candidates in the jet near-side with 1< p_T < 8 GeV/c in this analysis as an example.



FIG. 3:
 
The spin transfer $D _{TT}$ versus cos for a) $\Lambda$ and b) $\bar{\Lambda}$ hyperons, and c) the spin asymmetry $\delta_{TT}$ for the control sample of $K_S^0$ mesons versus cos/theta  in the $p_T$ bin of (2,3) GeV/c for triggered combined sample. The red circles show the results for positive pseudo-rapidity $\eta$ with respect to the polarized beam and the blue squares show the results for negative $\eta$. Only statistical uncertainties are shown.




FIG. 4:
 The spin transfer $D_\mathrm{TT}$ for $\Lambda$ and $\bar{\Lambda}$ versus $p_\mathrm{T}$ in polarized proton-proton collisions at $\sqrt{s}=200\,\mathrm{GeV}$ at STAR, in comparison with model predictions for (a) positive $\eta$ and (b) negative $\eta$. The vertical bars and bands indicate the sizes of the statistical and systematic uncertainties, respectively. The $\bar{\Lambda}$ results have been offset to slightly larger $p_T$ values for clarity.




Tables:


TABLE I:  Summary of selection cuts and the Λ and Λ̄ candidate counts and the residual background fractions in each pTbin. Here “DCA” denotes distance of closest approach, and N(σ) quantitatively measures the distance of a particle track to a certain particle band in dE/dx vs. rigidity space[28]. \ver{l} is representative of the vector from PV to Λ decay point and p⃗ is the reconstructed momentum of Λ.



Summary:
In summary, we report the first measurement on the transverse spin transfer, DTT, to Λ and Λ ̄ in transversely polarized proton-proton collisions at \sqrt{s} = 200 GeV at RHIC. The data correspond to an integrated luminosity of 18 pb1 taken at STAR experiment in the year of 2012, which cover mid-rapidity, |η| < 1.2 and pT up to 8GeV/cThe DTT value and precision at the highest pbin, where the effects are expected to be largest, are found to be DTT = 0.031 ± 0.033(stat.) ± 0.008(sys.) for Λ and DTT = 0.034 ± 0.040(stat.) ± 0.009(sys.) for Λ ̄ at η= 0.5 and pT= 6.7 GeV/cThe results for DTTare found to be consistent with zero for Λ and Λ̄ within uncertainties, and are also consistent with model predictions.
 
Paper draft and review:  
   Paper draft history
   Latest paper draft version:  paperDraft modified with PRD referee 

 
 PWGC review
   Collaboration review

Analysis Note:

   Analysis Note Draft

Support Materials:

   Web links:
  • Lambda reconstruction status
          1, Statistics of Lambda and anti-Lambda Reconstruction, Inclusive
          2,
 Statistics of Lambda and anti-Lambda Reconstruction, Jet near-side
  • MC production and data comparison
          1, MC production summary: hard_pT weight
          2, 
MC and data comparison for inclusive hyperons
          3, 
MC and data comparison for jet near-side hyperons
  • Trigger Bias

          1, Trigger bias parameters (fz_shift, feed-down fraction, fragmenting parton flavor fraction, subprocess fraction) plots 
          2, 
Uncertainty to D_TT from trigger bias

  Presentations:

  Proceedings:
Main Analysis Code: 



 

2012 Pi0 - Jet A_LL @ 500

 

2012 Pions in Jets A_UT @ 200 GeV

2012 dijet A_LL @ 500

2012/13 FMS A_LL @ 500 GeV

 

2013 Di-jet A_LL @ 500 GeV

 

A New Users Guide to PDSF Success

Credit goes to Kevin Adkins for the User's guide below:

With the current state of storage on RCF, several users are becoming regular users of PDSF. Anselm and others have requested that I write a short introduction to PDSF. So this blog will hold the keys for successful operation on PDSF. It will expand as issues are broght forth and addressed.

Getting started at PDSF:
1. Get your username at this website: https://nim.nersc.gov/nersc_account_request.php
Once you submit this form you will receive an email that includes a link. This link will only be valid for 72 hours, and will point you to a location where you can set your password. So don't postpone! If you have trouble the email will include a phone number to call, the staff is very helpful so don't hesitate to contact them.
2. Get logged in using the same terminal command as RCF:
ssh -Y username@pdsf.nersc.gov : where username, of course, will be your username.
3. When entering your password, you only have three chances. After your third chance you'll be "locked out" and you must call to have your password reset. To avoid the hassle, make your password something you can remember!

Storage disks at PDSF:
There are two disks that STAR-spin has access to on PDSF:
/eliza14/star/pwg/starspin/
/eliza17/star/pwg/starspin/
You must email Jeff Porter ( rjporter@bnl.gov ) with your username once you can log in. He will give you access to write on these disks. Once you have the access you can create yourself a folder to write your data to on one or both of the above disks.

Transferring data to PDSF:
PDSF has two Data Transfer Nodes (DTN) that are dedicated to the transfer of data at a high rate. These are
pdsfdtn1.nersc.gov
pdsfdtn2.nersc.gov
Transferring data is best with the rsync command. As an example, assume we have several subdirectories of jets stored in /star/data05/scratch/jkadkins/run12_Jets/ on RCF. To transfer this directory as is to the directory /eliza17/star/pwg/starspin/jkadkins/ on PDSF we would use:
rsync -r -v /star/data05/scratch/jkadkins/run12_Jets jkadkins@pdsfdtn1.nersc.gov:/eliza17/star/pwg/starspin/jkadkins/
Note that I left off the "/" at the end of the run12_Jets directory above. This means that we will copy all subdirectories to PDSF in the same structure. If the directory at PDSF doesn't exist, it will be created. If there is data already in a directory of the same name on PDSF then the new data will simply be added. If we had left "/" on the end of run12_Jets then we would have copied all files and subdirectories to /eliza17/star/pwg/starspin/jkadkins and not group it into a directory named run12_Jets on PDSF. Give it a test with a few files in a directory to see exactly how this works. 
Note: Transferring large volumes of data takes time. To transfer ~90 gigs of data it will take ~60 minutes. So transferring large jet trees or something similar can take a really long time. It may be best to break it up into smaller segments that are more time manageable.

Running code on PDSF:
Code runs EXACTLY the same on PDSF as it does on RCF. PDSF has the same CVS code up to date as on RCF (I'm not sure how often it's updated, but it's all there). So if you use code in CVS on RCF, then you can also use it on PDSF. The only thing that changes is that PDSF doesn't support is the STAR development library. So when running you'll need to use "starpro" or another library. 
Submitting jobs is also EXACTLY the same. You'll need an XML (if it works on RCF, it'll work on PDSF without changes) and you'll use the same star-submit command that you use on RCF. The changes come when you want to check the status of your jobs. The two most common commands to manage jobs are:
qstat -u username : Check the status of all jobs you have submitted
qdel -u username : Remove all jobs you currently have submitted
A full list of queue commands can be found here: http://www.nersc.gov/users/computational-systems/pdsf/using-the-sge-batch-system/monitoring-and-managing-jobs/

Finally, problems should be reported to the PDSF hypernews ( pdsf-hn@sun.star.bnl.gov ).

Analyses from the early years

 

(A) List of Physics Analysis Projects (obsolete)

Who Institution Data Topic
Jan Balewski MIT 2009 W production
Michael Betancourt MIT 2009/6   prompt gamma mid-rap A_LL/cross sec.
Alice Bridgeman ANL 2009 EEMC gammas
Thomas Burton Birmingham   2006 Lambda trans. pol.
Ramon Cendejas UCLA/LBL 2008 di-jet cross section
Ross Corliss MIT 2006/9 photons 1
Pibero Djawotho TAMU 2009 inclusive and di-jet
Xin Dong LBL    
Jim Drachenberg TAMU 2008 FMS+FTPC jets Sivers/Collins
Len Eun PSU 2006/8 eta SSA
Robert Fersch Kentucky 2009/6 tbd /mid-rapidity jet Collins
Oleksandr Grebenyuk LBL 2009/6 TBD/pi0
Weihong He IUCF 2006 EEMC pi0
Alan Hoffman MIT 2005/6 neutral pions A_LL
Liaoyuan Huo TAMU 2009 inclusive and di-jet
Christopher Jones MIT 2009/6 inclusive jets A_LL/cross section
Adam Kocoloski MIT 2005/6 charged pions A_LL
Priscilla Kurnadi UCLA 2006 non photonic electron A_LL
William Leight MIT 2009 Mid-rapidity hadron production
Xuan Li Shandong U   hyperons
Brian Page IUCF 2009 dijets
Donika Plyku ODU 2009 Spin dep. in pp elastic scattering from pp2pp
Nikola Poljak Zagreb 2006/8 Collins Sivers separation forward SSA
Tai Sakuma MIT 2005/6 dijets cross section/A_LL
Joe Seele MIT 2009 Ws and dijet cross section
Ilya Selyuzhenkov IUCF 2006-9 Forward gamma-jet
David Staszak UCLA 2006 Inclusive Jet A_LL
Justin Stevens IUCF 2010 TBD
Naresh Subba KSU 2006 Non-Photonic Elect. 1>eta>1.5 xsec
Matthew Walker MIT 2006/9 dijets cross section/A_LL
Grant Webb Kentucky 2009/6 mid-rap gamma or di-jet/ UEvent
Wei Zhou Shandong U   hyperons
Wei-Ming Zhang KSU 2008 non-photonic electrons EEMC A_LL

 

Common Analysis Trees

The Spin PWG maintains a set of trees connecting datasets from the various inclusive measurements in a way that allows for easy particle correlation studies. This page describes how to access the data in those trees.

Location

RCF:    /star/institutions/mit/common/run6/spinTree/
PDSF:   /auto/pdsfdv34/starspin/common/run6/spinTree/
Anywhere:   root://deltag5.lns.mit.edu//Volumes/scratch/common/run6/spinTree/spinAnalyses_runnumber.tree.root

The last option uses xrootd to access read-only files stored on an MIT server from any computer with ROOT installed.  If you have an Intel Mac note that ROOT versions 5.13.06 - 5.14.00 have a bug (patched in 5.14.00/b) that prevents you from opening xrootd files.

Interactive Mode

The basic trees are readable in a simple interactive ROOT session.  Each particle type is stored in a separate tree, so you need to use TTree::AddFriend to connect things together before you draw.  For example:

root [1] TFile::Open(&quot;root://deltag5.lns.mit.edu//Volumes/scratch/common/run6/spinTree/spinAnalyses_7156028.tree.root&quot;); root [2] .ls TXNetFile** root://deltag5.lns.mit.edu//Volumes/scratch/common/run6/spinTree/spinAnalyses_7156028.tree.root TXNetFile* root://deltag5.lns.mit.edu//Volumes/scratch/common/run6/spinTree/spinAnalyses_7156028.tree.root KEY: TProcessID ProcessID0;1 00013b6e-72c3-1640-a0e8-e5243780beef KEY: TTree spinTree;1 Spin PWG common analysis tree KEY: TTree ConeJets;1 this can be a friend KEY: TTree ConeJetsEMC;1 this can be a friend KEY: TTree chargedPions;1 this can be a friend KEY: TTree bemcPions;1 this can be a friend root [3] spinTree-&gt;AddFriend(&quot;ConeJets&quot;); root [4] spinTree-&gt;AddFriend(&quot;chargedPions&quot;); root [5] spinTree-&gt;Draw(&quot;chargedPions.fE / ConeJets.fE&quot;,&quot;chargedPions.fE&gt;0&quot;) If you have the class definitions loaded you can also access member functions directly in the interpreter:

root [6] spinTree-&gt;Draw(&quot;chargedPions.Pt() / ConeJets.Pt()&quot;,&quot;chargedPions.Pt()&gt;0&quot;)

Batch Mode

The StSpinTreeReader class takes care of all the details of setting branch addresses for the various particles behind the scenes.  It also allows you to supply a runlist and a set of triggers you're interested in, and it will only read in the events that you care about.  The code lives in

StRoot/StSpinPool/StSpinTree

and in the macros directory is an example showing how to configure it.  Let's look at the macro step-by-step:

//create a new reader StSpinTreeReader *reader = new StSpinTreeReader(); //add some files to analyze, one at a time or in a text file reader-&gt;selectDataset(&quot;$STAR/StRoot/StSpinPool/StSpinTree/datasets/run6_rcf.dataset&quot;); //reader-&gt;selectFile(&quot;./spinAnalyses_6119039.tree.root&quot;); Ok, so we created a new reader and told it we'd be using the files from Run 6 stored on RCF.  You can also give it specfic filenames if you'd prefer, but there's really no reason to do so.

//configure the branches you're interested in (default = true) reader-&gt;connectJets = true; reader-&gt;connectNeutralJets = false; reader-&gt;connectChargedPions = true; reader-&gt;connectBemcPions = true; reader-&gt;connectEemcPions = false; reader-&gt;connectBemcElectrons = false; //optionally filter events by run and trigger //reader-&gt;selectRunList(&quot;$STAR/StRoot/StSpinPool/StSpinTree/filters/run6_jets.runlist&quot;); reader-&gt;selectRun(7143025); //select events that passed hardware OR software trigger for any trigger in list reader-&gt;selectTrigger(137221); reader-&gt;selectTrigger(137222); reader-&gt;selectTrigger(137611); reader-&gt;selectTrigger(137622); reader-&gt;selectTrigger(5); //we can change the OR to AND by doing reader-&gt;requireDidFire = true; reader-&gt;requireShouldFire = true; In this block we configured the reader to pick up the jets, chargedPions and BEMC pi0s from the files. We also told it that we only wanted to analyze run 7132001, and that we only cared about events triggered by BJP1, L2jet, or L2gamma in the second longitudinal running period.  Finally, we required that one of those trigIds passed both the hardware and the software triggers.

After that, the reader behaves pretty much like a regular TChain.  The first time you call GetEntries() will be very slow (few minutes for the full dataset) as that's when the reader chains together the files and applies the TEventList with your trigger selection.  Each of the particles is stored in a TClonesArray, and the StJetSkimEvent is accessible via reader->event().

StJetSkimEvent *ev = reader-&gt;event(); TClonesArray *jets = reader-&gt;jets(); TClonesArray *chargedPions = reader-&gt;chargedPions(); TClonesArray *bemcPions = reader-&gt;bemcPions(); long entries = reader-&gt;GetEntries(); for(int i=0; i

What's Included?

Common trees are produced for both Run 5 and the 2nd longitudinal period of Run 6. Here's what available:

Run 5
  1. skimEvent
  2. ConeJets
  3. chargedPions
  4. bemcPions
Run 6
  1. skimEvent
  2. ConeJets12
  3. ConeJetsEMC
  4. chargedPions -- see (Data Collection)
  5. bemcPions
  6. bemcElectrons

Known Issues

The first time you read a charged pion (batch or interactive) you may see some messages like

Error in <tclass::new>: cannot create object of class StHelix</tclass::new>

These are harmless (somehow related to custom Streamers in the StarClassLibrary) but I haven't yet figured out how to shut them up.

42 runs need to be reprocessed for chargedPions in Run 5.  Will do once Andrew gives the OK at PDSF.

40 runs need to be reprocessed for Run 6 because of MuDst problems.  Murad has also mentioned some problems with missing statistics in the skimEvents and jet trees that we'll revisit at a later date.

Future Plans

Including EEMC pi0s and StGammaCandidates remains on my TO-DO list.  I've also added into StJet a vector of trigger IDs fired by that jet.  Of course we also need to get L2 trigger emulation into the skimEvent.  As always, if you have questions or problems please feel free to contact me.  

Cuts Summary

Here's a list of the cuts applied to the data in the common spin trees.

Run 5

Event
  • standard spinDB requirements
  • production triggers only
ConeJets
  • 0.2 < detEta < 0.8
  • 0.1 < E_neu / E_tot < 0.9
chargedPions
  • pt > 2
  • -1 < eta < 1
  • nFitPoints > 25
  • |DCA_global| < 1
  • -1 < nSigmaPion < 2
bemcPions
  • pt > 3.0
  • photon energies > 0.1
  • asymmetry < 0.8
  • 0.08 < mass < 0.25
  • charged track veto
  • BBC timebin in {7,8,9}

Run 6

Event
  • standard spinDB requirements
  • production triggers + trigId 5 (L2gamma early runs)
ConeJets, ConeJetEMC -- no cuts applied

chargedPions
  • pt > 2
  • -1 < eta < 1
  • nFitPoints > 25
  • |DCA_global| < 1
  • -1 < nSigmaPion < 2
bemcPions
  • pt > 5.2
  • photon energies > 0.1
  • asymmetry < 0.8
  • 0.08 < mass < 0.25
  • charged track veto
  • BBC timebin in {7,8,9} update:  timebin 6 added in 2007-07-18 production
  • both SMD planes good
bemcElectrons added as of 2007-07-18 production
  • hardware or software trigger in (117001, 137213, 137221, 5, 137222, 137585, 137611, 137622)
  • Global dE/dx cut changing with momentum
  • nFitPoints >= 15
  • nDedxPoints >= 10
  • nHits / nPoss >= 0.52
  • track Chi2 < 4
  • DCAGlobal < 2
  • NEtaStrips > 1 && NPhiStrips > 1
  • Primary dE/dx cut changing with momentum
  • 0.3 < P/E < 1.5
  • -0.01287 < PhiDist < 0.01345
  • ZDist in [-5.47,1.796] (West) or [-2.706,5.322] (East)

Introduction at Spin PWG meeting - 5/10/07

I've been working on a project to make the datasets from the various longitudinal spin analyses underway at STAR available in a common set of trees.  These trees would improve our ability to do the kind of correlation studies that are becoming increasingly important as we move beyond inclusive analyses in the coming years.

In our current workflow, each identified particle analysis has one or more experts responsible for deciding just which reconstruction parameters and cuts are used to determine a good final dataset.  I don't envision changing that.  Rather, I am taking the trees produced by those analyzers as inputs, picking off the essential information, and feeding it into a single common tree for each run.  I am also providing a reader class in StSpinPool that takes care of connecting the various branches and does event selection given a run list and/or trigger list.

Features

  • Readable without the STAR framework
  • Condenses data from several analyses down to the most essential ~10 GB (Run 6)
  • Takes advantage of new capabilities in ROOT allowing fast fill/run/trigger selection

Included Analyses

  • Event information using StJetSkimEvent
  • ConeJets12 jets (StJet only)
  • ConeJetsEMC jets (StJet only)
  • charged pions (StChargedPionTrack)
  • BEMC neutral pions (TPi0Candidate)
  • EEMC neutral pions (StEEmcPair?) -- TODO
  • electrons * -- TODO
  • ...

Current Status

I'm waiting on the skimEvent reproduction to finish before releasing.  I've got the codes to combine jets, charged pions, and BEMC pions, and I'm working with Jason and Priscilla on EEMC pions and BEMC electrons.

EEMC Direct Photon Studies (Pibero Djawotho, 2006-2008)

Everything as a single pdf file (341 pages, 8.2Mb)

2006.07.31 First Look at SMD gamma/pi0 Discrimination

 

Pibero Djawotho

 

Indiana University
July 31, 2006

Simulation

Simulation were done by Jason for the SVT review.

Maximal side residual

Figure 1: Fitted peak integral vs. fit residual sum (U+V) from st_jpsi input stream (J/psi trigger only). Figure 2: Fitted peak integral vs. fit residual sum (U+V) from st_physics input stream (all triggers except express stream triggers).

xy distribution of SMD hits

The separation between photons and pions was achieved by using Les cut in the above figures where photons reside above the curve and pions below. The data set used is the st_jpsi express stream.

Single peak characteristics

Fit function

The transverse profile of an electromagnetic shower in the SMD can be parametrized by the equation below in each SMD plane:

f(x) is the energy in MeV as a function of SMD strip x. The algorithm performs a simultaneous fit in both the U and V plane. The maximal residual (data - fit) is then calculated. A single photon in the SMD should be well descibed by the equation above and therefore will have a smaller maximal residual. A neutral pion, which decays into two photons, should exhibit a larger maximal residual. Typically, the response would be a double peak, possibly a larger peak and a smaller peak corresponding to a softer photon.

Single event SMD response

This directory contains images of single event SMD responses in both U and V plane. The file name convention is SMD_RUN_EVENT.png. The fit function for a single peak is the one described in the section above with 5 parameters:

  • p0 = yield (P0), area under the peak in MeV
  • p1 = mean (μ), center of peak in strips
  • p2 = sigma of the first Gaussian (w1)
  • p3 = fraction of the amplitude of the second Gaussian with respect to the first one (B), fixed to 0.2
  • p4 = ratio of the width of the second Gaussian to the width of the first one (w2/w1), fixed to 3.5

Code

macros

Documents

  1. Proposal to Contstruct an Endcap Calorimeter for Spin Physics at STAR
  2. Appendix Simulation Studies of Direct Photon Production at STAR
  3. An Endcap Calorimeter for STAR Conceptual Design Report
  4. The STAR Endcap Electromagnetic Calorimeter (EEMC NIM)
  5. An Endcap Calorimeter for STAR Technical Design Update #1
  6. Jan's gamma/pi0 algorithm
  7. Endcap Calorimeter Proposal (HTML @ IUCF)
  8. STAR Note 401: An Endcap Electromagnetic Calorimeter for STAR--Conceptual Design Report
  9. Spin Effects at Suppercollider Energies

2006.08.04 Second Look at SMD gamma/pi0 Discrimination

 

Second Look at SMD gamma/pi0 Discrimination

Pibero Djawotho
Indiana University
August 4, 2006

Dataset

The dataset used in this analysis is the 2005 p+p collision at √s=200 GeV with the endcap calorimeter high-tower-1 (eemc-ht1-mb = 96251) and high-tower-2 (eemc-ht2-mb = 96261) triggers.

The file catalog query used to locate the relevant files is:
get_file_list.pl -keys 'path,filename' -delim / -cond 'production=P05if, trgsetupname=ppProduction,filetype=daq_reco_MuDst,filename~st_physics, tpc=1,eemc=1,sanity=1' -delim 0

Results

SMD U and V Fits

Code

macros

2006.08.06 Comparison between EEMC fast and slow simulator

 

Comparison between EEMC fast and slow simulator

Pibero Djawotho
Indiana University
August 6, 2006

A detailed description of the EEMC slow simulator is presented at the STAR EEMC Web site.

The following settings were used in running the slow simulator:

  //--
  //-- Initialize slow simulator
  //--
  StEEmcSlowMaker *slowSim = new StEEmcSlowMaker("slowSim");
  slowSim->setDropBad(1);   // 0=no action, 1=drop chn marked bad in db
  slowSim->setAddPed(1);    // 0=no action, 1=ped offset from db
  slowSim->setSmearPed(1);  // 0=no action, 1=gaussian ped, width from db
  slowSim->setOverwrite(1); // 0=no action, 1=overwrite muDst values
  slowSim->setSource("StEvent");

  slowSim->setSinglePeResolution(0.1);
  slowSim->setNpePerMipSmd(2.0);
  slowSim->setNpePerMipPre(3.9);
  slowSim->setMipElossSmd(1.00/1000);
  slowSim->setMipElossPre(1.33/1000);

EEMC Fast Simulator

EEMC Slow Simulator

2006.09.15 Fit Parameters

 

Fit Parameters

Fit Function

The plots that follow are sums of individual SMD responses in each plane centered around a common mean (here 0), over a +/-40 strips range. The convention for the parameters in the fits below is:

  • p0=E -- area under the curve which represents energy in MeV
  • p1=μ -- mean
  • p2=σcore -- width of the narrow Gaussian
  • p3=γ -- relative contribution of the wide Gaussian to the area/height
  • p4=σtail -- width of the wide Gaussian

Simulation

The simulation is from single photons thrown at the EEMC with the following pT distribution:

The highest tower above 4 GeV in total energy is selected and the corresponding SMD sector fitted for peaks in both planes, where the area of the peaks in the U plane is constrained to be identical to that of the peak in the V plane. The peak is shifted to be centered at 0 where peaks from other events are then summed. The summed SMD response in each plane is displayed below:

Ditto in log scale.

Ditto by sector.

Fit Widths

Sector # SMD-u σcore SMD-u σtail SMD-v σcore SMD-v σtail
Sector 1 0.869033 ± 0.0142868 3.42031 ± 0.10226 0.84379 ± 0.0185107 3.03287 ± 0.0775009
Sector 2 0.814959 ± 0.0169271 2.99941 ± 0.0730426 0.889892 ± 0.0163065 3.35288 ± 0.0911979
Sector 3 0.84862 ± 0.0148706 3.07648 ± 0.0909689 0.914377 ± 0.014706 3.72821 ± 0.0966915
Sector 4 0.924398 ± 0.0144207 3.74458 ± 0.10611 0.888146 ± 0.0180771 3.06618 ± 0.0647075
Sector 5 0.934218 ± 0.0163887 3.45149 ± 0.0944309 0.911209 ± 0.0175273 3.28633 ± 0.0890581
Sector 6 0.797976 ± 0.0148133 3.20464 ± 0.0986085 0.822437 ± 0.018835 3.30595 ± 0.118813
Sector 7 0.836936 ± 0.0150085 3.28589 ± 0.0853598 0.873338 ± 0.0173883 3.16654 ± 0.0838938
Sector 8 0.828403 ± 0.0167005 3.05517 ± 0.075584 0.891045 ± 0.0152102 3.34806 ± 0.0836394
Sector 9 0.832881 ± 0.0127855 3.3214 ± 0.0762928 0.8436 ± 0.0175466 3.0183 ± 0.079444
Sector 10 0.804059 ± 0.0160906 3.0943 ± 0.0897946 0.874845 ± 0.015788 3.18113 ± 0.0748357
Sector 11 0.930286 ± 0.0187086 3.40024 ± 0.0951671 0.854395 ± 0.0167265 3.21076 ± 0.0812402
Sector 12 3.33227 ± 0.111911 0.848668 ± 0.0142344 0.895174 ± 0.0160939 3.48527 ± 0.12061

Data from 2005 pp200 EEMC HT 1 and 2 triggers

In this sample, high tower triggers, eemc-ht1-mb (96251) and eemc-ht2-mb (96261), from the 2005 p+p at √s=200 GeV ppProduction are selected. The highest tower above 4 GeV is chosen and the corresponding SMD sector is searched for peaks in both planes. Peaks from several events are summed together taking care of shifting them around to have a common mean.

Ditto in log scale.

Data from 2005 pp200 electrons

Here, I try to pick a representative sample of electrons from the 2005 pp200 dataset. The cuts used to pick out electrons are:

  • Epreshower1 > 5 MeV
  • Epreshower2 > 5 MeV
  • 0.75 < p/Etower < 1.25
  • 3 < dE/dx < 4 keV/cm

The selection for electrons is illustrated in the dE/dx plot below, where the pions should be on the left and the electrons on the right.


Pibero Djawotho
Last modified Tue Aug 15 10:41:19 EDT 2006

2007.02.05 Reconstructed/Monte Carlo Photon Energy

 

Reconstructed/Monte Carlo Photon Energy

This study is motivated by Weihong's photon energy loss study where an eta-dependence of reconstructed photon energy to generated photon energy in EEMC simulation was observed.

In this study, the eta-dependence is investigated by running the EEMC slow simulator with the new readjusted weights for the preshower and postshower layers of the EEMC. Details on this are here.

    • Fit to a constant

    • Fit to a line

    • Fit to a quadratic

    • Comparison between Weihong's and Pibero's results

    The parameters from the fits are used to plot the fit functions for comparison between Weihong's and Pibero's results.

      • Constant

      • Linear

      • Quadratic

    • Conclusion

    While the adjusted weights for the different EEMC layers contribute to bringing the ratio of reconstructed energy to generated energy closer to unity, they do not remove the eta-dependence.

    • References

    1. M. Albrow et al., NIM A 480 (2002) 524-546.
    2. R. Blair et al. (CDF Collaboration), CDF II Technical Design Report, FERMILAB-PUB-96-390-E, 1996.

    Pibero Djawotho
    Last updated Mon Feb 5 10:10:42 EST 2007

2007.02.08 E_reco / E_mc vs. eta

 

E_reco / E_mc vs. eta

Legend

  • black curve: before EEMC slow simulator
  • red curve: after EEMC slow simulator

Jason's Monte Carlo

  • 4.4k single gamma's
  • No SVT
  • Nominal vertex
  • Flat in pt 4-12 GeV

Will's Monte Carlo

  • 10k single gamma's
  • SVT/SSD out
  • Vertex at 0
  • Flat in pt 5-60 GeV

In the plot below, I use the energy of the single tower (tower with max energy) presumably the tower the photon hit. The nonlinearity seems to disappear.

In the plot below, I use the energy of the 3x3 cluster of tower centered around the tower with the max energy. The nonlinearity is restored.

The plot below shows Etower/Ecluster vs. eta where the cluster consists of 3x3 towers centered around the max energy tower.

Below is the profile of E_tower/E_cluster vs. eta.

The plot below shows the energy sampled by the entire calorimeter as a function of eta, i.e. sampling fraction as a function of eta.

Sampling fraction integrated over all eta's.


Pibero Djawotho
Last updated Thu Feb 8 13:59:29 EST 2007

2007.02.11 Reconstructed/Monte Carlo Muon Energy

 

Reconstructed/Monte Carlo Muon Energy

10k muons thrown by Will with:

  • zvertex=0
  • Flat in pT 5-60 GeV/c
  • Flat in η 1.1-2

zvertex

pT vs. η

EMC

Etower/EMC vs. η

Ecluster/EMC vs. η

Etowertanh(eta) vs. eta


Pibero Djawotho
Last modified Sun Feb 11 19:51:55 EST 2007

2007.02.15 160 GeV photons

 

160 GeV photons

 

  • 10k 160 GeV photons
  • zvertex=0
  • η range 0.8-2.2
  • SVT/SSD out


Pibero Djawotho
Last updated Thu Feb 15 04:33:09 EST 2007

2007.02.15 20 GeV photons

 

20 GeV photons

 

  • 10k 20 GeV photons
  • zvertex=0
  • η range 0.8-2.2
  • SVT/SSD out


Pibero Djawotho
Last updated Thu Feb 15 04:32:25 EST 2007

2007.02.15 80 GeV photons

 

80 GeV photons

 

  • 10k 80 GeV photons
  • zvertex=0
  • η range 0.8-2.2
  • SVT/SSD out


Pibero Djawotho
Last updated Thu Feb 15 03:16:54 EST 2007

2007.02.15 Reconstructed/Monte Carlo Electron Energy

 

Reconstructed/Monte Carlo Electron Energy

E=1 GeV

E=2 GeV


Pibero Djawotho
Last modified Thu Feb 15 00:42:30 EST 2007

2007.02.19 10 GeV photons

 

10 GeV photons

 

  • 10k 10 GeV photons
  • zvertex=0
  • η range 0.8-2.2
  • SVT/SSD out


Pibero Djawotho
Last updated Mon Feb 19 20:35:13 EST 2007

2007.02.19 40 GeV photons

 

40 GeV photons

 

  • 10k 40 GeV photons
  • zvertex=0
  • η range 0.8-2.2
  • SVT/SSD out


Pibero Djawotho
Last updated Mon Feb 19 20:37:37 EST 2007

2007.02.19 5 GeV photons

 

5 GeV photons

 

  • 10k 5 GeV photons
  • zvertex=0
  • η range 0.8-2.2
  • SVT/SSD out


Pibero Djawotho
Last updated Mon Feb 19 20:13:39 EST 2007

2007.02.19 Summary of Reconstructed/Monte Carlo Photon Energy

 

Summary of Reconstructed/Monte Carlo Photon Energy

 

Description

The study presented here uses Monte Carlo data sets generated by Will Jacobs at different photon energies (5, 10, 20, 40, 80, 160 GeV):

  • 10k photons
  • vertex at 0
  • eta 0.8-2.2
  • SVT/SSD out

For each photon energy, the ratio E_reco/E_MC vs. eta was plotted and fitted to the function p0+p1*(1-eta), where E_reco is the reconstructed photon energy integrated over the

entire

EEMC. The range of the fit was fixed from 1.15 to 1.95 to avoid EEMC edge effects. The advantage of parametrizing the eta-dependence of the ratio in this way is that p0 is immediately interpretable as the ratio in the middle of the EEMC. The parameters p0 and p1 vs. photon energy were subsequently plotted for the EEMC fast and slow simulator.

EEMC Fast/Slow Simulator Results

Conclusions

The parameter p0, i.e. the ratio E_reco/E_MC in the mid-region of the EEMC, increases monotonically from 0.74 at 5 GeV to 0.82 at 160 GeV, and the parameter p1, i.e. the slope of the eta-dependence, also increases monotonically from -0.035 at 5 GeV to 0.038 at 160 GeV. There appears to be a magic energy around 10 GeV where the response of the EEMC is nearly flat across its entire pseudorapidity range. The anomalous slope p1 at 160 GeV for the EEMC slow simulator is an EEMC hardware saturation effect. The EEMC uses 12-bit ADC's for reading out tower transverse energies and is set for a 60 GeV range. Any particle which deposits more than 60 GeV in E_T will be registered as depositing only 60 GeV as the ADC will return the maximum value of 4095. This translates into a limit on the eta range of the EEMC for a particular energy. Let's say that energy is 160 GeV and the EEMC tops at 60 GeV in E_T, then the minimum eta is acosh(160/60)=1.6. This limitation is noticeable in a plot of E_reco/E_MC vs. eta. This anomaly is not observed in the result of the EEMC fast simulator because the saturation behavior was not implemented at the time of the simulation (it has since been corrected). The energy-dependence of the parameter p0 is fitted to p0(E)=a+b*log(E) and the parameter p1 to p1(E)=a+b/log(E). The results are summarized below:

EEMC fast simulator fit p0(E)=a+b*log(E)
a = 0.709946 +/- 0.00157992
b = 0.022222 +/- 0.000501239

EEMC slow simulator fit p0(E)=a+b*log(E)
a = 0.733895 +/- 0.00359237
b = 0.0177537 +/- 0.0011397

EEMC fast simulator fit p1(E)=a+b/log(E)
a = 0.0849103 +/- 0.00556979
b = -0.175776 +/- 0.0138241

EEMC slow simulator fit p1(E)=a+b/log(E)
a = 0.0841488 +/- 0.0052557
b = -0.187769 +/- 0.0130445

Pibero Djawotho
Last updated Mon Feb 19 23:18:44 EST 2007

2007.05.24 gamma/pi0 separation in EEMC using linear cut

 

gamma/pi0 separation in EEMC using linear cut


Pibero Djawotho
Last updated Thu May 24 04:41:13 EDT 2007

2007.05.24 gamma/pi0 separation in EEMC using quadratic cut

 

gamma/pi0 separation in EEMC using quadratic cut


Pibero Djawotho
Last updated Thu May 24 04:41:13 EDT 2007

2007.05.24 gamma/pi0 separation in EEMC using quadratic cut

 

gamma/pi0 separation in EEMC using quadratic cut


Pibero Djawotho
Last updated Thu May 24 04:41:13 EDT 2007

2007.05.30 Efficiency of reconstructing photons in EEMC

 

Efficiency of reconstructing photons in EEMC

Monte Carlo sample

  • 10k photons
  • STAR y2006 geometry
  • z-vertex=0
  • Flat in pt 10-30 GeV
  • Flat in eta 1.0-2.1

SMD gamma/pi0 discrimination algorithm

The following

slide

from the IUCF STAR Web site gives a brief overview of the SMD gamma/pi0 discrimination algorithm using the method of maximal sided fit residual (data - fit). This technique comes to STAR EEMC from the Tevatron via Les Bland via Jason Webb. The specific fit function used in this analysis is:

f(x)=[0]*(0.69*exp(-0.5*((x-[1])/0.87)**2)/(sqrt(2*pi)*0.87)+0.31*exp(-0.5*((x-[1])/3.3)**2)/(sqrt(2*pi)*3.3))

x is the strip id in the SMD-u or SMD-v plane. The widths of the narrow and wide Gaussians are determined from empirical fits of shower shape response in the EEMC from simulation.

Optimizing cuts for gamma/pi0 separation

In the rest of this analysis, only those photons which have reconstructed pt > 5 GeV are kept. There is no requirement that the photon doesn't convert. The dividing curve between photons and pions is:

f(x)=4*x+1e-7*x**5

The y-axis is integrated yield over the SMD-u and SMD-v plane, and the x-axis is the sum of the maximal sided residual of the SMD-u and SMD-v plane.

Following exchanges with Scott Wissink, the idea is to move from a quintic to a quadratic to reduce the number of parameters. In addition, the perpendicular distance between the curve and a point in the plane is used to estimate the likelihood of a particle being a photon or pion. Distances above the curve are positive and those below are negative. The more positive the distance, the more likely the particle is a photon. The more negative the distance, the more likely the particle is a pion.

Hi Pibero,

With your new "linear plus quintic" curve (!) ... how did you choose the
coefficients for each term?  Or even the form of the curve?  I'm not
being picky, but how to optimize such curves will be an important issue
as we (hopefully soon) move on to quantitative comparisons of efficiency
vs purity.

As a teaser, please see attached - small loss of efficiency, larger gain
in purity.

Scott

Hi Pibero,

I just worked out the distance of closest approach to a curve of the form

    y(x) = a + bx^2

and it involves solving a cubic equation - so maybe not so trivial after
all.  But if you want to pursue this (not sure it is your highest
priority right now!), the cubic could be solved numerically and "alpha"
could be easily calculated.

More fun and games.

Scott
Hi Pibero,

I played around with the equations a bit more, and I worked out an
analytic solution.  But a numerical solution may still be better, since
it allows more flexibility in the algebraic form of the 'boundary' line
between photons and pions.

Here's the basic idea:  suppose the curved line that cuts between
photons and pions can be expressed as y = f(x).  If we are now given a
point (x0,y0) in the plane, our goal is to find the shortest distance to
this line.  We can call this distance d (I think on your blackboard we
called it alpha).

To find the shortest distance, we need a straight line that passes
through (x0,y0) and is also perpendicular to the curve f(x).  Let's
define the point where this straight line intersects the curve as
(x1,y1).  This means (comparing slopes)

    (y1 - y0) / (x1 - x0) = -1 / f'(x1)

where f'(x1) is the derivative of f(x) evaluated at the point (x1,y1). 
Rearranging this, and using y1 = f(x1), yields the general result

    f(x1) f'(x1)  -  y0 f'(x1)  +   x1  -   x0  =  0

So, given f(x) and the point (x0,y0), the above is an equation in only
x1.  Solve for x1, use y1 = f(x1), and then the distance d of interest
is given by

    d = sqrt[ (x1 - x0)^2 + (y1 - y0)^2 ]

Example:  suppose we got a reasonable separation of photons and pions
using a curve of the form

    y = f(x) = a + bx^2

Using this in the above general equation yields the cubic equation

    (2b^2) x1^3  +  (2ab + 1 - 2by0) x1  -  x0  =  0

Dividing through by 2b^2, we have an equation of the form

    x^3 + px + q = 0

This can actually be solved analytically - but as I mentioned, a
numerical approach gives us more flexibility to try other forms for the
curve, so this may be the way to go.  I think (haven't proved
rigorously) that for positive values of the constants a, b, x0, and y0,
the cubic will yield three real solutions for x1, but only one will have
x1 > 0, which is the solution of interest.

Anyway, it has been an interesting intellectual exercise!

Scott

I made use of the ROOT function TMath::RootsCubic to solve the cubic equation numerically for computing distances of each point to the curve. With the new quadratic curve f(x)=100+0.1*x^2 the efficiency is 63% and the rejection is 82%.

Efficiency and Rejection

The plot on the left below shows the efficiency of identifying photons over the pt range of 10-30 GeV and the one on the right shows the rejection rate of single neutral pions. Both average about 75% over the pt range of interest.

Rejection vs. efficiency at different energies

The plot below shows background rejection vs. signal efficiency for different energy ranges of the thrown gamma/pi0.

Rejection vs. efficiency with preshower cut

Below on the left is a plot of the ratio of the sum of preshower 1 and 2 to tower energy for both photons (red) and pions (blue). On the right is the rejection of pions vs. efficiency of photons as I cut on the ratio of preshower to tower. It is clear from these plots that the preshower layer is not a good gamma/pi0 discriminator, although can be used to add marginal improvement to the separation preovided by the shower max.

ALL ENERGIES

E=20-40 GeV

E=40-60 GeV

E=60-80 GeV

E=80-90 GeV


Pibero Djawotho
Last updated Wed May 30 00:32:16 EDT 2007

2007.06.12 gamma/pi0 separation in EEMC at pT 5-10 GeV

 

gamma/pi0 separation in EEMC at pT 5-10 GeV


Pibero Djawotho
Last updated Tue Jun 12 11:59:42 EDT 2007

2007.06.28 Photons in Pythia

Pythia Simulations

 

Pythia Simulations


All partonic pT

The plots below show the distribution of clusters in the endcap calorimeter for different partonic pT ranges. 2000 events were generated for each pT range. A cluster is made up of a central high tower above 3 GeV in pT and its surounding 8 neighbors. The total cluster pT must exceed 4.5 GeV.

pT=9-11 GeV

Below is the pT of direct and decay photons from the Pythia record. Note how the two subsets are well separated at a given partonic pT. Any contamination to the direct photon signal would have to come from higher partonic pT.

Differences between Renee's and Manuel's Pythia records?

Number of prompt photons per event from GEANT record


Pibero Djawotho
Last updated Fri Jun 8 16:08:27 EDT 2007

a_LL

 

Partonic aLL

Jet

Gamma


Pibero Djawotho
Last updated Sat Jun 30 20:14:21 EDT 2007

gamma pT=9-11 GeV

 

gamma pT=9-11 GeV


Pibero Djawotho
Last modified Fri Jul 6 10:48:39 EDT 2007

gamma-jet kinematics

 

gamma-jet kinematics


Clusters without parent track

Pibero Djawotho
Last updated Thu Jun 28 04:43:57 EDT 2007

gamma/X separation by energy

 

gamma/X separation by energy


Pibero Djawotho
Last updated Wed Jul 11 11:10:26 EDT 2007

gamma/X separation by energy with pT weights

 

gamma/X separation by energy with pT weights


Pibero Djawotho
Last updated Thu Jul 12 00:28:35 EDT 2007

gamma/X separation by energy with pT weights and normalized by number of events

 

gamma/X separation by energy with pT weights and normalized by number of events


Pibero Djawotho
Last updated Wed Jul 18 14:55:08 EDT 2007

gamma/pi0 separation efficiency and rejection at pT=5-7 GeV

 

gamma/pi0 separation efficiency and rejection at pT=5-7 GeV



Pibero Djawotho
Last updated Wed Jul 4 17:45:26 EDT 2007

gamma/pi0 separation efficiency and rejection at pT=9-11 GeV

 

gamma/pi0 separation efficiency and rejection at pT=9-11 GeV



Pibero Djawotho
Last updated Wed Jul 4 13:23:41 EDT 2007

gamma/pi0 separation efficiency and rejection at pT=9-11 GeV

 

gamma/pi0 separation efficiency and rejection at pT=9-11 GeV



Pibero Djawotho
Last updated Wed Jul 4 13:23:41 EDT 2007

2007.07.09 How to run the gamma fitter

 

How to run the gamma fitter


The gamma fitter runs out of the box. The code consists of the classes StGammaFitter and StGammaFitterResult in CVS. After checking out a copy of offline/StGammaMaker, cd into the offline directory and run:

root4star StRoot/StGammaMaker/macros/RunGammaFitterDemo.C

The following plots will be generated on the ROOT canvas and dumped into PNG files.


Pibero Djawotho
Last modified Mon Jul 9 18:40:07 EDT 2007

2007.07.25 Revised gamma/pi0 algorithm in 2006 p+p collisions at sqrt(s)=200 GeV

 

Revised gamma/pi0 algorithm in 2006 p+p collisions at sqrt(s)=200 GeV


Description

The class

StGammaFitter

computes the maximal sided residual of the SMD response in the u- and v-plane for gamma candidates. It is based on C++ code developed by Jason Webb from the original code by Les Bland who got the idea from CDF (?) The algorithm follows the steps below:

  1. The SMD response, which is SMD strips with hits in MeV, in each plane (U and V) is stored in histogram hU and hV.
  2. Fit functions fU and fV are created. The functional form of the SMD peak is a double-Gaussian with common mean and fixed widths. The widths were obtained by the SMD response of single photons from the EEMC slow simulator. As such, the only free parameters are the common mean and the total yield. The actual formula used is: [0]*(0.69*exp(-0.5*((x-[1])/0.87)**2)/(sqrt(2*pi)*0.87)+0.31*exp(-0.5*((x-[1])/3.3)**2)/(sqrt(2*pi)*3.3))
    • [0] = yield
    • [1] = mean
  3. The mean is fixed to the strip with maximum energy and the yield is adjusted so the height of the fit matches that of the mean.
  4. The residual for each side of the peak is calculated by subtracting the fit from the data (residual = data - fit) from 2 strips beyond the mean out to 40 strips.
  5. The maximal sided residual is the greater residual of each side.

Code

Candidates selection

  • 2006 p+p at 200 GeV dataset from Sivers analysis (from Jan Balewski)
    /star/institutions/iucf/balewski/prodOfficial06_muDst/
  • Gamma candidate from gamma maker: 3x3 clusters with pt > 5 GeV
  • No track pointing to cluster
  • Minimum of 3 SMD hits in each plane
  • Cuts from Jan & Naresh electron analysis:
    • Preshower 1 energy > 0.5 MeV
    • Preshower 2 energy > 2.0 MeV
    • Postshower energy < 0.5 MeV
  • The triggers caption in the PDF files shows the trigger id's satisfied by the event. A red trigger id is a L2-gamma trigger. I observe that generally the L2-gamma triggered event are a bit cleaner. Also shown is the pt and energy of the cluster.

Raw SMD response

  1. No additional cuts
  2. Pick only L2-gamma triggers
  3. Pick only L2-gamma triggers but no jet patch trigger
  4. Make isolation cut (see below)

The parameters of the isolation cut were suggested by Steve Vigor:

Hi Pibero,

  In general, I believe people have used smaller cone radii for isolation
cuts than for jet reconstruction (where the emphasis is on trying to
recover full jet energy).  So you might try something like requiring
that no more than 10 or 20% of the candidate cluster E_T appears
in scalar sum p_T for tracks and towers within a cone radius of
0.3 surrounding the gamma candidate centroid, excluding the
considered cluster energy.  The cluster may already contain energy
from other jet fragments, but that should be within the purview of
the gamma/pi0 discrimination algo to sort out.  For comparison, Les
used a cone radius of 0.26 for isolation cuts in his original simulations
of gamma/pi0 discrimination with the endcap.  Using much larger
cone radii may lead to accidental removal of too many valid gammas.


Steve


Pibero Djawotho
Last updated Wed Jul 25 10:07:07 EDT 2007

2007.09.12 Endcap Electrons

 

Endcap Electrons


This analysis is based on the work of Jan and Justin on SMD Profile Analysis for different TPC momenta. See here for a list of cuts. The original code used by Jan and Justin is here.

    • Transverse running

    • Analysis uses 64 out of 300 runs from 2006 pp transverse run
    • MuDst are located at:
      /star/institutions/iucf/balewski/prodOfficial06_muDst/
    • No trigger selection

    Figure 1: Number of tracks surviving each successive cut

    Figure 2a: Number of tracks per trigger id for all electron candidates. Most common trigger ids are:

    127652 eemc-jp0-etot-mb-L2jet EEMC JP > th0 (32, 4 GeV) and ETOT > TH (109, 14 GeV), minbias condition, L2 Jet algorithm, reading out slow detectors, transverse running
    127271 eemc-jp1-mb EEMC JP > th1 (49, 8 GeV) && mb, reading out slow detectors, transverse running
    127641 eemc-http-mb-l2gamma EEMC HT > th1 (12, 2.6 GeV, run < 7100052;13, 2.8 GeV, run >=7100052) and TP > TH1 (17, 3.8 GeV, run < 710052; 21, 4.7 GeV, run>=7100052 ), minbias condition, L2 Gamma algorithm, reading out slow detectors, L2 thresholds at 3.4, 5.4, transverse running
    127622 bemc-jp0-etot-mb-L2jet BEMC JP > th0 (42, 4 GeV) and ETOT > TH (109, 14 GeV), minbias condition, L2 Jet algorithm, reading out slow detectors, transverse running; L2jet thresholds at 8.0,3.6,3.3

    Figure 2b: Number of tracks per trigger id for all electron candidates for pT > 4 GeV. The dominant trigger ids become:

    127641 eemc-http-mb-l2gamma EEMC HT > th1 (12, 2.6 GeV, run < 7100052;13, 2.8 GeV, run >=7100052) and TP > TH1 (17, 3.8 GeV, run < 710052; 21, 4.7 GeV, run>=7100052 ), minbias condition, L2 Gamma algorithm, reading out slow detectors, L2 thresholds at 3.4, 5.4, transverse running
    127262 eemc-ht2-mb-emul EEMC HT > th2 (22, 5.0 GeV) && mb, reading out slow detectors, emulated in L2, transverse running, different threshold from 117262
    127271 eemc-jp1-mb EEMC JP > th1 (49, 8 GeV) && mb, reading out slow detectors, transverse running
    127652 eemc-jp0-etot-mb-L2jet EEMC JP > th0 (32, 4 GeV) and ETOT > TH (109, 14 GeV), minbias condition, L2 Jet algorithm, reading out slow detectors, transverse running

    Figure 3: pT distribution of tracks before E/p, dE/dx and pT cut

    Figure 4: pT distribution of electron candidates with pT > 4 GeV

    Figure 5: η distribution of electron candidates (all pT)

    Figure 6: φ distribution of electron candidates (all pT)

    Figure 7: dE/dx of tracks before E/p and dE/dx cuts (all pT)

    Figure 8: dE/dx of tracks before E/p and dE/dx cuts (pT > 4 GeV)

    Figure 9: dE/dx of tracks before E/p and dE/dx cuts (all pT and 0.8 < η < 1.0)

    Figure 10: dE/dx of tracks before E/p and dE/dx cuts (all pT and 1.0 < η < 1.2)

    Figure 11: dE/dx of tracks before E/p and dE/dx cuts (all pT and 1.2 < η < 1.4)

    Figure 12: dE/dx of tracks before E/p and dE/dx cuts (all pT and 1.4 < η < 1.6)

    Figure 13: dE/dx of tracks before E/p and dE/dx cuts (all pT and 1.6 < η < 1.8)

    Figure 14: dE/dx of tracks before E/p and dE/dx cuts (all pT and 1.8 < η < 2.0)

    • Click here for SMD profiles of transverse electron candidates.
    • Click here for ROOT file with transverse electrons ntuple.

    • Longitudinal running

    • MuDst are located at:
      /star/institutions/iucf/hew/2006ppLongRuns/
      

    Figure 2.1

    Figure 2.2: The dominant trigger ids are:

    137273 eemc-jp1-mb EEMC JP > th1 (52, 8.7 GeV) && mb, reading out slow detectors, longitudinal running 2
    137641 eemc-http-mb-l2gamma EEMC HT > th1 (16, 3.5 GeV) and TP > th1 (20, 4.5 GeV), minbias condition, L2 Gamma algorithm, reading out slow detectors, L2 thresholds at 3.7, 5.2, longitudinal running 2
    137262 eemc-ht2-mb-emul EEMC HT > th2 (22, 5.0 GeV) && mb, reading out slow detectors, emulated in L2, longitudinal running 2
    137222 bemc-jp1-mb BEMC JP > th1 (60, 8.3 GeV) && mb, reading out slow detectors, longitudinal running 2

    Figure 2.3a

    Figure 2.3

    Figure 2.4

    Figure 2.5

    Figure 2.6

    Figure 2.7

    Figure 2.8

    Figure 2.9

    Figure 2.10

    • Click here for SMD profiles of longitudinal electron candidates.
    • Click here for ROOT file with longitudinal electrons ntuple.

    • Code

    Click here for a tarball of the code used in this analysis.

    SMD response function

    • f(x)=p0*(0.69*exp(-0.5*((x-p1)/0.87)**2)/(sqrt(2*pi)*0.87)+0.31*exp(-0.5*((x-p1)/3.3)**2)/(sqrt(2*pi)*3.3))
      
    • p0 = yield
    • p1 = centroid

    Transverse

    21 electrons

    Longitudinal

    99 electrons


Pibero Djawotho
Last updated Wed Sep 12 08:29:53 EDT 2007

2008.01.23 Endcap etas

 

Endcap etas

Endcap etas

This analysis to look for etas at higher energy is in part motivated by this study. The interest in etas, of course, is that their decay photons are well separated at moderate energies (certainly more separated than the photons from pi0 decay). I ran Weihong's pi0 finder with tower seed threshold of 0.8 GeV and SMD seed threshold of 5 MeV (I believe his default SMD seed setting is 2 MeV). I then look in the 2-photon invariant mass region between 0.45 and 0.65 GeV (the PDG nominal mass for the eta is 0.54745 +/- 0.00019 GeV). I observe what looks like a faint eta peak. The dataset processed is the longitudinal 2 run of 2006 from the 20 runs sitting on the IUCF disk in Weihong's directory (/star/institutions/iucf/hew/2006ppLongRuns/).

Within the reconstructed mass window 0.45 to 0.65 GeV, I take a look at the decay photon shower profiles in the SMD. The samples are saved in the file etas.pdf. For the most part, these shower shapes are cleaner than the original sample. Although the statistics are not great.

Additional Material

Documents


Pibero Djawotho
Last updated Wed Jan 23 12:35:43 EST 2008

2008.02.27 ESMD shape library

 

ESMD shape library


Shower Widths for Monte Carlo and Data

Description

Hal did a comparison of the widths of the shower shapes between Monte Carlo and data. Below is a description of what was done.

      I took the nominal central value, either from the maxHit or the
nominal central value, and added the energy in the +/- 12 strips.  Then I
computed the mean strip (which may have been different from the nominal
central value!!).  I normalized the shape to give unit area for each smd
cluster, and added to the histograms separately for U and V and for MC and
data (= Will's events).  I did NOT handle Will's events correctly, just
using whatever event was chosen randomly, rather than going through his
list sequentially.  Note I ran 1000 events, and got 94 events in my shower
shape histos.

      So, there are several minor problems.  1) I didn't go through Will's
events sequentially.  2) I normalized, but perhaps not to the correct 25
strips, because the mean strip and the nominal strip may have differed.
3) there may have been a cutoff on some events due to being close to one
end of the smd plane (near strip 0 or 287).  My sense from looking at the
plots is that these don't matter much.

      The conclusion is that the MC shape is significantly narrower than
the shape from Will's events, which is obviously narrower than the random
clusters we were using at first with no selection for the etas.  Hence, we
are not wasting our time with this project.

Decsription of Pythia Sample

A few histograms were added to the code:

  • MC is Pythia gamma-jet at partonic pT 9-11 GeV with gamma in the Endcap
  • Data is from Will Jacobs golden events from Weihong sample
  • Require no conversion
  • Require all hits from direct photon in same sector


Figure 1:

Data vs. MC mean u-strip



Figure 2:

Data vs. MC mean v-strip



Figure 3:

Data vs. MC u-strip sigma



Figure 4:

Data vs. MC v-strip sigma



Figure 5:

MC E

v

vs. E

u

Figure 6:

Data E

v

vs. E

u

Figure 7:

MC energy asymmetry in SMD planes



Figure 8:

Data energy asymmetry in SMD planes



Figure 9:

Shower shape library index used (picked at random)

 

Single events shower shapes are displayed in

esmd.pdf

or

esmd_solid.pdf

.

  • green = projected position of direct photon in the Endcap
  • blue = Monte Carlo SMD response
  • red = Data SMD response

Hal Spinka
Pibero Djawotho
Last modified Wed Feb 27 09:51:27 EST 2008

2008.02.28 ESMD QA for run 7136033

 

ESMD QA for run 7136033



Pibero Djawotho
Last updated Thu Feb 28 16:17:55 EST 2008

2008.03.04 A second look at eta mesons in the STAR Endcap Calorimeter

 

A second look at eta mesons in the STAR Endcap Calorimeter


Introduction

In case you missed it, the first look is

here

. I processed

44 runs

from the 2006 pp longitudinal 2 runs and picked events tagged with the L2gamma trigger id (137641). I ran the StGammaMaker on the MuDst files from these runs and produced gamma trees. These gamma trees are available at

/star/institutions/iucf/pibero/2007/etaLong/

. Within the StGammaMaker framework, I developed code to seek candidate etas with emphasis on high purity. The macros and source files are:

Note, the workhorse function is

StEtaFinder::findTowerPoints()

.

Algorithm

  1. Find seed tower with pT > 0.8 GeV
  2. Require no TPC track into the seed tower
  3. Get the ranges of SMD U & V strips that span the volume of the seed tower
  4. Find the strips with maximum energy within these ranges
  5. Require that the maximum strips have more than 2 MeV in each SMD plane
  6. Get the intersection of the maximum strips and ensures that it lies within 70% of the fiducial volume of the seed tower
  7. Make sure the photon candidate responsible for the SMD clusters above enters and exits the same seed tower
  8. Form a 11-strip cluster in each plane with +/-5 strips around the max strip and require that it contains 70% of the energy in a range +/-20 strips around the max strip
  9. Require that the energy asymmetry between the 11-strip clusters in the U and V planes be less than 20%
  10. Create a point using the energy of the seed tower and the position of the intersection of the max strips in the SMD U and V planes
  11. Repeat until seed towers in the event are exhausted
  12. Combine different points in the event to calculate the invariant mass
  13. Diphoton pairs with invariant mass between 0.4 and 0.6 GeV are saved to a PDF file

Invariant mass

I fit the diphoton invariant mass with two Gaussians, one for the pi0 peak (p0-p2) and another one for the eta peak (p3-p5) plus a quadratic for the background (p6-p8). The Gaussian is of the form p0*exp(0.5*((x-p1)/p2)**2) and the quadratic is of the form p6*+p7*x+p8*x**2. A slightly better chi2/ndf in the fit is achieved by using Breit-Wigner functions instead of Gaussians for the signal here. I calculate the raw yield of etas from the fit as p3*sqrt(2*pi)*p5/bin_width = 85 where each bin is 0.010 GeV wide. I select candidate etas in the mass range 0.45 to 0.55 GeV and plot their photon response in the shower maximum detector here. Since we are interested in collecting photons of pT > 7 GeV, only those candidate photons with pT > 5 GeV will be used in the shower shape library. I also calculate the background under the signal region by integrating the background fit from 0.45 to 0.55 GeV and get 82 counts.

  • S = 85
  • B = 82
  • S:B = 1.03:1
  • S/√S+B = 6.6

Additional plots

 

2008.03.08 Adding the SMD energy to E_reco/E_MC for Photons

 

Adding the SMD energy to E_reco/E_MC for Photons

The following is a revisited study of E_reco/E_MC for photons with the addition of the SMD energy to E_reco.

QA plots for each energy

  1. 5 GeV
  2. 10 GeV
  3. 20 GeV
  4. 40 GeV
  5. 80 GeV
  6. 160 GeV

E_SMD/E_reco vs. eta



Pibero Djawotho
Last updated Thu Mar 8 04:27:28 EST 2007

2008.03.21 Chi square method

Chi square method

 

[IMG] SectorVsRunNumber.png   10-Feb-2010 12:22   14K  
[IMG] ShowerShapes.png        10-Feb-2010 12:22   17K  
[IMG] chiSquareMC.png         10-Feb-2010 12:22   13K  
[IMG] chiSquarePibero.png     10-Feb-2010 12:22   16K  
[IMG] chiSquareWill.png       10-Feb-2010 12:22   16K  
[IMG] chiSquareWillAndMC.png  10-Feb-2010 12:22   17K  

 

2008.04.08 Data-Driven Shower Shapes

 

Data-Driven Shower Shapes


Gamma Conversion before the Endcap

The plots below show the conversion process before the Endcap. I look at prompt photons heading towards the Endcap from a MC gamma-jet sample with a partonic pT of 9-11 GeV. I identify those photons that convert using the GEANT record. The top left plot shows the total number of direct photons and those that convert. I register a 16% conversion rate. This is consistent with Jason's 2006 SVT review. The top right plot shows the source of conversion, where most of the conversions emanate from the SVT support cone, also consistent with Jason's study. The bottom left plot shows the separation in the SMD between the projected location of the photon and the location of the electron/positron from conversion.

Shower shapes comparison

This

PDF

file shows several shower shapes in a single plot for comparison:

  • MC - Monte Carlo shower shape from the 9-11 GeV pT gamma-jet Pythia sample
  • DD - Data-driven Monte Carlo shower shape (Each final state photon shower shape is replaced with a corresponding shower shape from data in the same sector configuration, energy, preshower, and U/V-plane bin).
  • Standard MC - Monte Carlo shower shape parametrized by Hal (also from the 9-11 GeV pT gamma-jet Pythia sample)
  • Will - Data shower shape derived from photons from eta decays by Will using a modified version of Weihong/Jason meson pi0 finder
  • Pibero - Data shower shape derived from photons from eta decays by Pibero using a crude eta finder

Shower Shapes Sorted by SMD Plane, Sector Configuration, Energy and Preshower

These Shower Shapes are binned by:

  1. SMD plane (U and V)
  2. Sector configuration with the formula sector%3 where sector=1..12, so 3 different bins. More details can be found at the EEMC Web site under the Geometry link.
  3. Energy of the photon (E < 8 GeV and E > 8 GeV)
  4. Preshower energy (pre1==0&amp;&amp;pre2==0) and (pre1&gt;0||pre2&gt;0)

They are then fitted with a triple-Gaussian of the form:

[0]*([2]*exp(-0.5*((x-[1])/[3])**2)/(sqrt(2*pi)*[3])+[4]*exp(-0.5*((x-[1])/[5])**2)/(sqrt(2*pi)*[5])+(1-[2]-[4])*exp(-0.5*((x-[1])/[6])**2)/(sqrt(2*pi)*[6]))

Comparison of Sided Residuals for Monte Carlo (MC) and Data-Driven (DD) Shower Shapes

All fits to MC are with reference to the old Monte carlo fit function:

[0]*(0.69*exp(-0.5*((x-[1])/0.87)**2)/(sqrt(2*pi)*0.87)+0.31*exp(-0.5*((x-[1])/3.3)**2)/(sqrt(2*pi)*3.3))

All fits to the data are with reference to a single

Shower Shape

. The fit function is:

[0]*([2]*exp(-0.5*((x-[1])/[3])**2)/(sqrt(2*pi)*[3])+[4]*exp(-0.5*((x-[1])/[5])**2)/(sqrt(2*pi)*[5])+(1-[2]-[4])*exp(-0.5*((x-[1])/[6])**2)/(sqrt(2*pi)*[6]))

  1. All Shower Shapes
  2. No Conversion
  3. Conversion
  4. No Preshower
  5. Preshower
  6. No Conversion and Preshower
  7. Sector Configuration 0
  8. Sector Configuration 1
  9. Sector Configuration 2

Comparison of Sided Raw Tails for Monte Carlo (MC) and Data-Driven (DD) Shower Shapes

  1. All Shower Shapes
  2. No Conversion
  3. Conversion
  4. No Preshower
  5. Preshower
  6. No Conversion and Preshower
  7. Sector Configuration 0
  8. Sector Configuration 1
  9. Sector Configuration 2

Pibero Djawotho
Last updated Tue Apr 8 17:29:40 EDT 2008

2008.04.12 Data-Driven Residuals

 

Data-Driven Residuals


Gammas

Jets

Background Rejection vs. Signal Efficiency

Partonic pT=9-11 GeV Partonic pT=9-11 GeV

Background Rejection vs. Signal Efficiency (Neutral Meson pT > 8 GeV)


Pibero Djawotho
Last updated Sat Apr 12 13:27:50 EDT 2008

2008.04.12 Pythia Gamma-Jets

 

Pythia Gamma-Jets


Gamma-Jet Yields

During Run 6, the L2-gamma trigger (trigger id 137641) sampled 4717.10 nb-1 of integrated luminosity. By restricting the jet to the Barrel, |ηjet|<1, and the gamma to the Endcap, 1<ηgamma<2, the yield of gamma-jets is estimated as the product of the luminosity, the cross section, and the fraction of events in the phasespace above. The total cross section reported by Pythia for gamma-jet processes at different partonic pT thresholds is listed in the table below. No efficiencies are included.

pT threshold [GeV] Total cross section [mb] Fraction Ngamma-jets
5 6.551E-05 0.0992 30654
6 3.075E-05 0.1161 16840
7 1.567E-05 0.1150 8500
8 8.654E-06 0.1131 4617
9 4.971E-06 0.1223 2868
10 2.953E-06 0.1151 1603

Gamma-Jets pT slope

The pT slope is exp(-0.69*pT)=2^(-pT), so the statistics are halved with each 1 GeV increase in pT.

References

  1. Yield estimates based on single-particle MC sample, and comparison w/ pythia (Jason Webb)
  2. Pythia estimates of gamma-jet yields (Jim Sowinski)

Pibero Djawotho
Last updated Sat Apr 12 15:15:56 EDT 2008

2008.04.16 Jet Finder QA

 

Jet Finder QA

Pibero Djawotho
Last updated Wed Apr 16 08:33:01 EDT 2008

2008.04.20 BUR 2009

Partonic pT=7-9 GeV

Partonic pT=9-11 GeV

Combined Partonic pT

2008.04.22 Run 6 Photon Yield Per Trigger

 

Run 6 Photon Yield Per Trigger


Introduction

The purpose of this study is to estimate the photon yield per trigger in the Endcap Electromagnetic Calorimeter during Run 6. The trigger of interest is the L2-gamma trigger. Details of the STAR triggers during Run 6 were compiled in the 2006 p+p run (run 6) Trigger FAQ by Jamie Dunlop. The triggers relevant to this study are reproduced in the table below for convenience.

Trigger id Trigger name Description
117641 eemc-http-mb-l2gamma EEMC HT > th1 (12, 2.6 GeV) and TP > TH1 (17, 3.8 GeV), minbias condition, L2 Gamma algorithm, reading out slow detectors, L2 thresholds at 2.9, 4.5
127641 eemc-http-mb-l2gamma EEMC HT > th1 (12, 2.6 GeV, run < 7100052;13, 2.8 GeV, run >=7100052) and TP > TH1 (17, 3.8 GeV, run < 710052; 21, 4.7 GeV, run>=7100052 ), minbias condition, L2 Gamma algorithm, reading out slow detectors, L2 thresholds at 3.4, 5.4, transverse running
137641 eemc-http-mb-l2gamma EEMC HT > th1 (16, 3.5 GeV) and TP > th1 (20, 4.5 GeV), minbias condition, L2 Gamma algorithm, reading out slow detectors, L2 thresholds at 3.7, 5.2, longitudinal running 2

The luminosity sampled by each trigger was also caclulated here by Jamie Dunlop. The luminosity for the relevant triggers is reproduced in the table below for convenience. The figure-of-merit (FOM) is calculated as FOM=Luminosity*PB*PY for transverse runs and FOM=Luminosity*PB2*PY2 for longitudinal runs where PB is the polarization of the blue beam and PY is the polarization of the yellow beam. Naturally, in spin physics, the FOM is the better indicator of statistical precisison.

Trigger First run Last run Luminosity [nb-1] Figure-of-merit [nb-1]
117641 7093102 7096017 118.88 11.89
127641 7097009 7129065 3219.04 1099.43
137641 7135050 7156028 4717.10 687.65

Event selection

Trigger selection

For this study, only the trigger of longitudinal running 2 (137641) is used. As mentioned above, at level-0, an EEMC high tower above 3.5 GeV and its associated trigger patch above 4.5 GeV in transverse energy coupled with a minimum bias condition, which is simply a BBC coincidence to ensure a valid collision, is required for the trigger to fire. The EEMC has trigger patches of variable sizes depending on their location in pseudorapidity. (The BEMC has trigger patches of fixed sizes, 4x4 towers.) At level-2, a high tower above 3.7 GeV and a 3x3 patch above 5.2 GeV in transverse energy is required to accept the event.

Gamma candidates

In addition to selecting events that were tagged online by the L2-gamma trigger, the offline

StGammaMaker

looks for tower clusters with minimum transverse energy of 5 GeV. These clusters along with their associated TPC tracks, preshower and postshower tiles, and SMD strips form gamma candidates. Gamma trees for the 2006 trigger ID 137641 with primary vertex are located at

/star/institutions/iucf/pibero/2006/gammaTrees/

.

Track isolation

The gamma candidate is required to have no track pointing to any of its towers.

EMC isolation

The gamma candidate is required to have 85% of the total transverse energy in a cone of radius 0.3 in eta-phi space around the position of the gamma candidate. That is E

Tgamma

/E

Tcone

> 0.85 and R=√Δη

2

+Δφ

2

=0.3 is the cone radius.

Jet Reconstruction

The gamma candidate is matched to the best away-side jet with neutral fraction < 0.9 and cos(φ

gamma

jet

) < -0.8. The 2006 jet trees are produced by Murad Sarsour at PDSF in

/eliza13/starprod/jetTrees/2006/trees/

. A local mirror exists at RCF under the directory

/star/institutions/iucf/pibero/2006/jetTrees/

.

Spin Information

Jan Balewski has an excellent write-up, Offline spin DB at STAR, on how to get spin states. I obtain the spin states from the skim trees in the jet trees directory. In brief, the useful spin states are:

Blue Beam Polarization Yellow Beam Polarization Spin4
P P 5
P N 6
N P 9
N N 10

Event Summary

L2-gamma triggers 730128
Endcap gamma candidates 723848
Track isolation 246670
EMC isolation 225400
Away-side jet 99652
SMD max sided residual 19281
Barrel-only jet 15638

Note the number of L2-gamma triggers include only those events with a primary vertex and at least one gamma candidate (BEMC or EEMC).

Gamma-Jet Plots

 
 

Comparison of pT Slope with Pythia

Partonic Kinematics Reconstruction

Open Questions

  1. I count ~2.4M events with trigger id 137641 using the Run 6 Browser, however my analysis only registers about ~0.78M.

Pibero Djawotho
Last updated Tue Apr 22 11:40:18 EDT 2008

2008.05.07 Number of Jets

 

Number of Jets


After selecting Endcap gamma candidates out of L2-gamma triggers, applying track and EMC isolation cuts, and matching the Endcap gamma candidate to an away-side jet, I record the number of jets below per event. Surprisingly, 8% of the events only have 1 jet. Those are events where the Endcap gamma candidate was not reconstructed as a neutral jet by the jet finder. The question is why.

I display both Barrel and Endcap calorimeter towers (the z-axis represents tower energy) and draw a circle of radius 0.3 around the gamma candidate and a circle of radius 0.7 around the away-side jet for 2006 pp200 run 7136022. Even though many of the gamma candidates not reconstructed by the jet finder are at the forward edge of the Endcap, it is not at all clear why those that are well within the detector are not being reconstructed.


Pibero Djawotho
Last updated Wed May 7 09:54:32 EDT 2008

2008.05.09 Gamma-jets pT distributions

 

Gamma-jets pT distributions


Note:

No cuts on residuals applied.

Not cut on number of towers in gamma cluster

Number of towers in gamma cluster <= 9

Number of towers in gamma cluster <= 4

Number of towers per cluster distributions

Gamma candidates xy-distribution

z-vertex distribution

Eta distribution

Phi distribution

log10(E_post/E_tow) distribution

pT asymmetry

References

  1. Ilya's pT distributions
  2. Michael's weigthing of simulation

Pibero Djawotho
Last updated Fri May 9 08:19:00 EDT 2008

2008.05.19 Binning the shower shape library

 

Binning the shower shape library


Distributions

Shower Shapes


Pibero Djawotho
Last updated Mon May 19 12:09:48 EDT 2008

2008.06.03 Jet A_LL Systematics

 

Jet A_LL Systematics


Hypernews discussion

jet A_LL systematic possibility

References

  1. I.P. Auer et al, Phys.Rev.D 32(1985)1609
  2. J. Bystricky et al, J.Phys. France 39(1978)1

Pibero Djawotho
Last updated Tue Jun 3 15:35:24 EDT 2008

2008.06.18 Photon-jet reconstruction with the EEMC - Part 2 (STAR Collaboration Meeting - UC Davis)

2008.07.16 Extracting A_LL and DeltaG

 

Extracting A_LL and DeltaG


Determining state of beam polarization for Monte Carlo events

While Pythia does a pretty good job of simulating prompt photon production in p+p collisions, it does not include polarization for the colliding protons nor partons. A statistical method for assigning polarization states for each event based on ALL [1] is demonstrated in this section. For an average number of interactions for each unpolarized bunch crossing, Neff, the occurence of an event with a particular polarization state obeys a Poisson distribution with average yield of events per bunch crossing:

For simplicity, the polarizations of the blue and yellow beams are assumed to be P

B

=P

Y

=0.7 and N

eff

=0.01. The "+" spin state defines the case where both beams have the same helicities and the "-" spin state for the case of opposite helicities. The asymmetry A

LL

is calculated from the initial states polarized and unpolarized parton distribution functions and parton-level asymmetry:

The algorithm then consists in alternatively drawing a random value N

int

from the Poisson distributions with mean μ

+

and μ

-

until N

int

>0 at which point an interaction has occured and the event is assigned the current spin state. The functioning of the algorithm is illustrated in Figure 1a where an input A

LL

=0.2 was fixed and N

trials

=500 different asymmetries were calculated. Each trial integrated N

total

=300 events. It is then expected that the mean A

LL

~0.2 and the statistical precision~0.1:

Indeed, both the A

LL

and its error are reproduced. In addition, variations on the number of events per trial were investigated (N

total

) in Figure 1b. The extracted width of the Gaussian distribution for A

LL

is consistent with the prediction for the error (red curve).

  • ROOT macro used to generate Figure 1a SimALL.C
  • ROOT macro used to generate Figure 1b SimALL2.C
Figure 1a Figure 1b

Event reconstruction

For this study, the gamma-jets Monte Carlo sample for all partonic pT were used. As an example, the prompt photon processes for the partonic pT bin 9-11 GeV and their total cross sections are listed in the table below. Each partonic pT bin was divided into 15 files each of 2000 events.

 ==============================================================================
 I                                  I                            I            I
 I            Subprocess            I      Number of points      I    Sigma   I
 I                                  I                            I            I
 I----------------------------------I----------------------------I    (mb)    I
 I                                  I                            I            I
 I N:o Type                         I    Generated         Tried I            I
 I                                  I                            I            I
 ==============================================================================
 I                                  I                            I            I
 I   0 All included subprocesses    I         2000          9365 I  3.074E-06 I
 I  14 f + fbar -> g + gamma        I          331          1337 I  4.930E-07 I
 I  18 f + fbar -> gamma + gamma    I            2             8 I  1.941E-09 I
 I  29 f + g -> f + gamma           I         1667          8019 I  2.579E-06 I
 I 114 g + g -> gamma + gamma       I            0             1 I  1.191E-10 I
 I 115 g + g -> g + gamma           I            0             0 I  0.000E+00 I
 I                                  I                            I            I
 ==============================================================================

The cross sections for the different partonic pT bins has been tabulated by Michael Betancourt and is reproduced here for convenience.

Partonic pT [GeV] Cross Section [mb]
3-4 0.0002962
4-5 0.0000891
5-7 0.0000494
7-9 0.0000110
9-11 0.00000314
11-15 0.00000149
15-25 0.000000317
25-35 0.00000000990
35-45 0.000000000449

These events were processed through the 2006 pp200 analysis chain, albeit without any cuts on the SMD. The simulated quantities were taken from the Pythia record and the reconstructed ones from the analysis.

Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9

Partonic kinematics reconstruction

PartonicKinematics.C
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15 (a)
Figure 15 (b): quark from proton 1 (blue beam, +z direction)
Figure 15 (c): quark from proton 1 (blue beam, +z direction) and q + g -> q + gamma subprocess (29)
Figure 15 (d): quark from proton 1 (blue beam, +z direction) and q + qbar -> gamma + g subprocess (14)

Predictions for A_LL and direct determination of DeltaG(x)

DeltaG.C
Figure 16 (a)
Figure 16 (b): quark from proton 1 (blue beam, +z direction)
Figure 16 (c): quark from proton 1 (blue beam, +z direction) and q + g -> q + gamma subprocess (29)
Figure 16 (d): quark from proton 1 (blue beam, +z direction) and q + qbar -> gamma + g subprocess (14)

References

  1. Appendix Simulation Studies of Direct Photon Production at STAR
  2. DeltaG(x,mu^2) from jet and prompt photon production at RHIC arXiv:hep-ph/0005320

Pibero Djawotho
Last updated Wed Jul 16 10:29:22 EDT 2008

2008.07.20 How to install Pythia 6 and 8 on your laptop?

 

How to install Pythia 6 and 8 on your laptop?


    • Install Pythia 6 and build the interface to ROOT

    Download the file pythia6.tar.gz from the ROOT site ftp://root.cern.ch/root/pythia6.tar.gz and unpack.
    tar zxvf pythia6.tar.gz
    
    A directory pythia6/ will be created and some files unpacked into it. Cd into it and compile the Pythia 6 interface to ROOT.
    cd pythia6/
    ./makePythia6.linux
    
    For more information, consult Installing ROOT from Source and skip to the section Pythia Event Generators.

    • Install Pythia 8

    Download the latest version of Pythia from http://home.thep.lu.se/~torbjorn/Pythia.html and unpack.
    tar zxvf pythia8108.tgz
    
    A directory pythia8108/ will be created. Cd into it and follow the instructions in the README file to build Pythia 8. Set the environment variables PYTHIA8 and PYTHIA8DATA (preferably in /etc/profile.d/pythia8.sh):
    export PYTHIA8=$HOME/pythia8108
    export PYTHIA8DATA=$PYTHIA8/xmldoc
    
    Run configure with the option for shared-library creation turned on.
    ./configure --enable-shared
    make
    

    • Install ROOT from source

    Download the source code for ROOT from http://root.cern.ch/ and compile.
    tar zxvf root_v5.20.00.source.tar.gz
    cd root/
    ./configure linux --with-pythia6-libdir=$HOME/pythia6 \
      --enable-pythia8 \
      --with-pythia8-incdir=$PYTHIA8/include \
      --with-pythia8-libdir=$PYTHIA8/lib
    make
    make install
    
    Set the following environment variables (preferably in /etc/profile.d/root.sh):
    export ROOTSYS=/usr/local/root
    export PATH=$PATH:$ROOTSYS/bin
    export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$ROOTSYS/lib:/usr/local/pythia6
    export MANPATH=$MANPATH:$ROOTSYS/man
    
    You should be good to go. Try running the following Pythia 6 and 8 sample macros:
    root $ROOTSYS/tutorial/pythia/pythiaExample.C
    root $ROOTSYS/tutorial/pythia/pythia8.C
    

Pibero Djawotho
Last updated on Sun Jul 20 23:35:39 EDT 2008

2008.07.23 Hot Strips Identified by Hal Spinka

 

Hot Strips Identified by Hal Spinka


    • Run 7136034 Sector 8

    Strips 08U020, 08U080, 08V185 and 08V225

    • Run 7137036 Sector 9

    Strips 09V064


    Pibero Djawotho
    Last updated Wed Jul 23 03:40:54 EDT 2008

2008.07.24 Strips from Weihong's 2006 ppLong 20 runs

 

Strips from Weihong's 2006 ppLong 20 runs


Energy [GeV] vs. strip id

2006ppLongRuns.pdf

Raw ADC vs. strip id

7136022.pdf 7136033.pdf 7136034.pdf 7137036.pdf 7138001.pdf 7138010.pdf 7138032.pdf 7140046.pdf 7143012.pdf 7144014.pdf 7145018.pdf 7145024.pdf 7146020.pdf 7146077.pdf 7147052.pdf 7148027.pdf 7149005.pdf 7152062.pdf 7153008.pdf 7155052.pdf


Pibero Djawotho
Last updated Thu Jul 24 10:35:50 EDT 2008

G/h Discrimination Algorithm (Willie)

My blog pages, from first to last:

01/25: http://drupal.star.bnl.gov/STAR/blog-entry/wleight/2008/jan/25/photon-analysis-progress-week-1-21-08-1-25-08.  This post discusses the problem with the spike in secondary tracks at eta=1 in our single-particle simulations.

01/28: http://drupal.star.bnl.gov/STAR/blog-entry/wleight/2008/jan/28/further-qa-plots.  This post has QA plots for every particle sample Ross generated, both in the barrel and in the endcap.

02/01: http://drupal.star.bnl.gov/STAR/blog-entry/wleight/2008/feb/01/more-qa-plots-time-efficiencies.  This post has QA plots for gamma and piminus (barrel and endcap) as well as reconstruction efficiencies.

02/04: http://drupal.star.bnl.gov/STAR/blog-entry/wleight/2008/feb/04/photon-qa-efficiency-plots-error-bars.  This post adds error bars to the reconstruction efficiencies for the photon barrel sample.

02/05: http://drupal.star.bnl.gov/STAR/blog-entry/wleight/2008/feb/05/first-clustering-plots.  This post has the first clustering plots, for muons and gammas (barrel only), showing cluster energy, energy-weighted cluster eta and phi, and the number of seeds and clusters passing the thresholds for each event.

02/12: http://drupal.star.bnl.gov/STAR/blog-entry/wleight/2008/feb/12/preshower-plots.  This post has preshower plots from the gamma barrel sample, but the plots are of all preshowers in the event and use the preshower information generated by the BEMC simulator and so are not useful.

02/13: http://drupal.star.bnl.gov/STAR/blog-entry/wleight/2008/feb/13/more-clustering-plots.  This post has geant QA plots combined with the clustering plots from 02/05 above, but for the gamma and piminus barrel samples.

02/19: http://drupal.star.bnl.gov/STAR/blog-entry/wleight/2008/feb/19/cluster-track-matching-plots.  This post investigates the cluster-to-track matching for the gamma barrel sample, using a simple distance variable d=sqrt((delta eta)^2+(delta phi)^2)) to match clusters to tracks and plotting the resulting energy distributions, the energy ratio, etc.

02/21: http://drupal.star.bnl.gov/STAR/blog-entry/wleight/2008/feb/21/more-preshower-plots.  This post plots preshower distributions but uses the preshower information from the BEMC simulator and so is not useful.

02/28: http://drupal.star.bnl.gov/STAR/blog-entry/wleight/2008/feb/28/further-preshower-plots-not-completed-yet.  Figures 1, 3, and 5 in this post plot the geant preshower energy deposition for gammas, piminuses, and muons (Figs 2, 4, and 6 plot reconstructed preshower information again and so are not useful).

03/04: http://drupal.star.bnl.gov/STAR/blog-entry/wleight/2008/mar/04/muon-preshower-plots.  This post expands on the post of 02/28, with additional plots using the geant preshower information, including preshower cluster energy vs. tower cluster energy.

03/06: http://drupal.star.bnl.gov/STAR/blog-entry/wleight/2008/mar/06/first-physics-cuts.  This post basically recaps the previous post and adds a cut: unfortunately the cut is based partly on the thrown particle energy and so is not useful.

03/18: http://drupal.star.bnl.gov/STAR/blog-entry/wleight/2008/mar/18/smd-qa-plots.  This post plots energy-weighted SMD phi and eta distributions, as well as the total energy deposited in the BSMDE and BSMDP strips located behind a cluster.

03/28: http://drupal.star.bnl.gov/STAR/blog-entry/wleight/2008/mar/28/smd-clustering-plots.  This post contains SMD clustering plots for barrel gamma and piminus samples.

Neutral Pions 2005: Frank Simon

Information about the 2005 Spin analysis (focused on A_LL and <z>, some QA plots for cross section comparisons) will be archived here. The goal is obviously the 2005 Pi0 spin paper.

Invariant Mass and Width: Data-MC

Here I show the invariant masses and corresponding widths I obtain using my cross section binning. These are compared to MC values.

The Method:

  • Invariant mass Data histograms (low mass background and combinatoric background subtracted) are fitted with a gaussian in the range 0.1 - 0.18 GeV/c^2. This gives the mass (gaussian mean) and width (gaussian sigma)
  • MC invariant mass histograms are obtained from correctly associated MC Pi0s after reconstruction. No weighting of the different partonic pt samples is performed. This can (and will) introduce a bias
    • Then the same fitting procedure as for data is applied

The results are shown in the two figures below.

Mass:

 

Width:

 

 

 

Neutral Pion Paper: 2005 ALL & <z>

Neutral Pion Paper for 2005 data: Final Results.

There are two spin plots planned for the paper, one with the 2005 A_LL and one with the <z>. In addition to this the cross section will be included (analysis by Oleksandr used for publication).

 

Final result for A_LL:

 

Figure 1: Double longitudinal spin asymmetry for inclusive Pi0 production. The curves show predictions from NLO pQCD calculations based on the gluon distributions from the GRSV, GS-C and DSSV global analyses. The systematic error shown by the gray band does not include a 9.4% normalization uncertainty due to the polarization measurement.

 

The chi2/ndf for the different model curves are:

GRSV Std: 0.740636
GRSV Max: 3.49163
GRSV Min: 0.94873
GRSV Zero: 0.546512
GSC: 0.513751
DSSV: 0.543775

 

 

Final Result for <z>:

Figure 2: Mean momentum fraction of Pi0s in their associated jet as a function of p_T for electromagnetically triggered events. The data points are plotted at the bin center in pion p_T and are not corrected for acceptance or trigger effects. Systematic errors, estimated from a variation of the cuts, are shown by the grey band underneath the data points. The lines are results from simulations with the PYTHIA event generator. The solid line includes detector effects simulated by GEANT, while the dotted line uses jet finding on the PYTHIA particle level. The inset shows the distribution of pT, π / pT, Jet for one of the bins, together with a comparison to PYTHIA with a full detector response simulation.

 

Below are links to details about the two results.

 

<z> Details

<z> Details

 

The goal of this analysis is to relate the neutral pions to the jets they are embedded in. The analysis is done using the common spin analysis trees, which provide the necessary tools to combine the jet and neutral pion analysis.

A neutral pion is associated to a parent jet if it is within the jet cone of 0.4 in eta and phi. To avoid edge effects in the detector, only neutral pions with 0.3 < eta < 0.7 are accepted. 

 

Cut details:

E_neutral / E_total < 0.95

higher energy photon of Pi0 > 2.8 GeV (HT1 trigger); > 3.6 GeV (HT2 trigger)

combination HT1/HT2: below 5.7 GeV only HT1 is used, above that both HT1 and HT2 are accepted

 

The final result uses both HT1 and HT2 triggers, but a trigger separated study has also been done, as shown below. There, HT2 includes only those HT2 triggers that do not satisfy HT1 (because of prescale).

Figure 1: <z> for Pi0 in jets as a function of p_T for HT1 and HT2 triggers. Also shown is the mean jet p_T as a function of pion p_T.

 

Bin-by-Bin momentum ratio

Figure 2: Bin-by-bin ratio of pion to jet p_T. The <z> is taken from the mean of these distributions, the error is the error on the mean. A small fraction of all entries have higher Pi0 p_T than jet p_T. Similar behavior is also observed for Pythia MC with GEANT jets. This obviously increases the <z>. An alternative would be to reject those events. The agreement with MC becomes worse if this is done.

 

Here is the data - MC comparison for 3 of the above bins. For the simulation, the reconstruction of the Pi0 is not required to keep statistics reasonable, so the true Pi0 pt is used. However, the MC jet finding uses all momenta after Geant, this is why the edges are "smoother" in the MC plot than in the data plots. Since <z> is an average value, this is not expected to be affected by this, since on average the Pi0 pt is reconstructed right.

Figure 3: Data / MC for Bin 5: 6.7 to 8 GeV

Figure 4: Data / MC for Bin 6: 8 to 10 GeV

Figure 5: Data / MC for Bin 7: 10 to 12 GeV

 

 

 

 

A_LL Details

Details on the A_LL result and the systematic studies:

The result in numbers:

Bin <p_T> [GeV] in bin A_LL stat. error syst. error
1 4.17 0.01829 0.03358 0.01603
2 5.41 -0.01913 0.02310 0.01114
3 7.06 0.00915 0.03436 0.01343
4 9.22 -0.06381 0.06366 0.01862

 

A_LL as separated by trigger:

Figure 1: A_LL as a function of p_T for HT1 (black) and HT2 (red) triggers separately. HT1 here is taken as all triggers that satisfy the HT1 requirement, but not HT2. Since the HT2 prescale is one, there are very little statistics for HT1 at the highest p_T. The highest p_T point for HT1 is outside the range of the plot, and has a large error bar. The high p_T HT1 data is used in the combined result. 

 

Systematics: Summary

 

  Bin 1 Bin 2 Bin 3 Bin4
relative luminosity 0.0009 0.0009 0.0009 0.0009
non-longitudinal pol. 0.0003 0.0003 0.0003 0.0003
beam background 0.0012 0.0084 0.0040 0.0093
yield extraction 0.0144 0.0044 0.0102 0.0116
invariant mass background 0.0077 0.0061 0.0080 0.0108
total 0.01603 0.01114 0.01343 0.01862

The first two systematics are common to all spin analyses. The numbers here are taken from the jet analysis. No Pi0 non-longitudinal analysis has been performed due to lacking statistics. These systematics are irrelevant compared to the others.

The analysis specific systematics are determined from the data, and as such are limited by statistics. The real systematic limit of a Pi0 analysis with a very large data sit will be much lower.

For the yield extraction systematic the invariant mass cuts for the pion yield extraction are varied. The systematic is derived from the maximum change in asymmetry with changing cuts.

For the beam background, the systematic is derived by studying how much A_LL changes when the beam background is removed. This is a conservative estimate that covers the scenario that only half of the background is actually removed. The asymmetry of the background events is consistent with zero.

For the invariant mass background systematic, A_LL is extracted in three invariant mass bins outside the signal region. The amount of background under the invariant mass peak (includes combinatorics, low mass and others) is estimated from the invariant mass distribution as shown below. For all three bins, the background A_LL is consistent with zero, a "worst case" of value + 1 sigma is assumed as deviation from the signal A_LL.

Invariant mass distribution:

Figure 2: Invariant mass distribution for HT1 events, second p_T bin. The red lines are the MC expectations for Pi0 and Eta, the green line is low mass background, the magenta line is combinatoric background, the thick blue line is a pol2 expectation for the other background, the blue thinner line is the total enveloppe of all contributions, compared to the data. At low mass, the background is overestimated.

 

Other systematic studies: False Asymmetries

 

False asymmetries (parity-violating single spin asymmetries) were studied to exclude systematic problems with spin asignments and the like. Of course the absence of problems in the jet analysis with the same data set makes any issues very unlikely, since jet statistics allow much better verifications than Pi0s. Still, single spin asymmetries were studied, and no significant asymmetries were observed. For both triggers, both asymmetries (yellow and blue) and for all p_T bins the asymmetries are consistent with zero, in most cases within one sigma of zero. So there are no indications for systematic effects. The single spin asymmetries are shown below:

Figure 3: Single spin asymmetry epsilon_L for the blue beam.

Figure 4: Single spin asymmetry epsilon_L for the yellow beam.

Neutral strange particle transverse asymmetries (tpb)

Neutral strange particle transverse asymmetry analysis

Here is information regarding my analysis of transverse asymmetries in neutral strange particles using 2006 p + p TPC data. This follows-on from and expands upon the earlier analysis I did, which can still be found at star.bnl.gov/protected/strange/tpb/analysis/. Comments, questions, things-you'd-like-to-see-done and so forth are welcomed. I'll catalogue updates in my blog as I make them.

The links listed below are in 'analysis-order'; best to use these for navigation rather than the alphabetically listed links Drupal links below/in the sidebar.

  1. Data used
  2. V0 decays
  3. Energy loss particle identification
  4. Geometrical cuts
  5. Single spin asymmetry with cross formula
  6. SSA using relative luminosity
  7. Double spin asymmetry

e-mail me at tpb@np.ph.bham.ac.uk




Data used

Data used in analysis

Data used for this analysis is 2006 p+p 200 GeV data taken with transverse polarisation, trigger setup "ppProductionTrans". This spanned days 97 (7th April) to 129 (9th May) inclusive. Trigger bemc-jp0-etot-mb-l2jet (ID 127622) is used. A file catalogue query with the following conditions gives a list of runs for which data is available:

trgsetupname=ppProductionTrans,tpc=1,year=2006,sanity=1,collision=pp200,
magscale=FullField,filename~physics,library=SL06e,production=P06ie

This generates a list of 549 runs. These runs are then compared against the spin PWG run QC (see http://www.star.bnl.gov/protected/spin/sowinski/runQC_2006) and are rejected if any of the following conditions are true:

  • The run is marked as unusable
  • The run has a jet patch trigger problem
  • The run has a spin bits problem
  • The run is unchecked

This excludes 172 runs, leaving 377 runs to be analysed.

I use a Maker class to create TTrees of event objects with V0 and spin information for these runs. Code for the Maker and Event classes can be found at /star/u/tpb/StRoot/StTSAEventMaker/ and /star/u/tpb/StRoot/StV0NanoDst/ respectively. Events are accepted only if they fulfill the following criteria:

  • Event contains specified trigger ID
  • StSpinDbMaker::isMaskedUsingBx48() returns false
  • StSpinDbMaker::offsetBX48minusBX7() returns zero

TTrees are produced for 358 runs (19 produce no/empty output), yielding 2,743,396 events.

The vertex distribution of events from each run are then checked by spin bits. A Kolmogorov test (using ROOT TH1::KolmogorovTest) is used to compare the vertex distributions for (4-bit) spin bits values 5, 6, 9 and 10. If any of the distributions are inconsistent, the run is rejected. Each run's mean event vertex z position is then plotted. Figure 1 shows the distribution, fitted with a Gaussian. A 3σ cut is applied and outlier runs rejected. 38 runs are rejected by these further cuts. The remaining 320 runs, spanning 33 RHIC fills and comprising 2,500,421 events, are used in the analysis.

Run-wise mean event vertex z distribution. It is well fitted by a Gaussian distribution.
Figure 1: Mean event vertex z for each run. The red lines indicate the 3σ cut.



Double spin asymmetry

Double spin asymmetry

I measure a double spin asymmetry defined as follows

A_TT=[N(parallel)-N(antiparallel)]/[N(parallel)+N(antiparallel)]
Equation 1

where N-(anti)parallel indicates yields measured in one half of the detector when the beam polarisations are aligned (opposite) and P1 and P2 are the polarisations of the beams. Accounting for the relative luminosity, these yields are given by

N(parallel)=N(upUp)/R4+N(downDown)
Equation 2
N(antiparallel)=N(upDown)/R5+N(downUp)/R6
Equation 2

where the arrows again indicate beam polarisations. Figures one and two show the fill-by-fill measurement of ATT, corrected by the beam polarisation, summed over all pT.

Straight-line fit to fill-by-fill measurement of K0s A_TT
Figure 1: K0S ATT fill-by-fill
Straight-line fit to fill-by-fill measurement of Lambda A_TT
Figure 2: Λ ATT fill-by-fill



Energy loss identification

Energy loss particle identification

The Bethe-Bloch equation can be used to predict charged particle energy loss. Hans Bichsel's model adds to this and the Bichsel function predictions for particle energy loss are compared with measured values. Tracks with dE/dx sufficiently far from the predicted value are rejected. e.g. when selecting for Λ hyperons, the positive track is required to have dE/dx consistent with that of a proton, and the negative track consistent with that of a π-minus.

The quantity σ = sqrt(N) x log( measured dE/dx - model dE/dx ) / R is used to quantify the deviation of the measured dE/dx from the model value. N is the number of track hits used in dE/dx determination and R is a resolution factor. A cut of |σ| < 3 applied to both V0 daughter tracks was found to significantly reduce the background with no loss of signal. Figures one to three below show the invariant mass distriubtions of the V0 candidates accepted and rejected and table one summarises the results of the cut. Background rejection is more successful for (anti-)Λ than for K0S because most background tracks are pions; the selection of an (anti-)proton daughter rejects the majority of the background tracks.


Invariant mass spectrum of V0 candidates passing K0s dE/dx cut
Figure 1a: Invariant mass spectrum of V0 candidates under K0s hypothesis passing dE/dx cut
Invariant mass spectrum of V0 candidates failing K0s dE/dx cut
Figure 1b: Invariant mass spectrum of V0 candidates under K0s hypothesis failing dE/dx cut
Invariant mass spectrum of V0 candidates passing Lambda dE/dx cut
Figure 2a: Invariant mass spectrum of V0 candidates under Λ hypothesis passing dE/dx cut
Invariant mass spectrum of V0 candidates failing Lambda dE/dx cut
Figure 2b: Invariant mass spectrum of V0 candidates under Λ hypothesis failing dE/dx cut
Invariant mass spectrum of V0 candidates passing anti-Lambda dE/dx cut
Figure 3a: Invariant mass spectrum of V0 candidates under anti-Λ hypothesis passing dE/dx cut
Invariant mass spectrum of V0 candidates failing anti-Lambda dE/dx cut
Figure 3b: Invariant mass spectrum of V0 candidates under anti-Λ hypothesis failing dE/dx cut


Species Pass (millions) Fail (millions) % pass
K0S 95.5 48.9 66.2 %
Λ 32.5 111.9 22.5 %
anti-Λ 11.8 132.5 8.2 %

Table 1




Geometrical cuts

Geometrical cuts

Energy loss cuts are successful in eliminating a significant portion of the background, but further reduction is required to give a clear signal. In addition final yields are calculated by a bin counting method, which requires that the background around the signal peak has a straight line shape. Therefore additional cuts are placed on the V0 candidates based on the geometrical properties of the decay. There are five quantities on which I chose to cut:

  • Distance of closest approach (DCA) of the V0 candidate to the primary vertex: if the V0 candidate is a genuine particle, its momentum vector should track back to the interaction point. Spurious candidates will not necessarily do so, therefore an upper limit is placed on the approach distance of the V0 to the interaction point.
  • DCA between the daughter tracks: due to detector resolution the daughter tracks never precisely meet, but placing an upper limit of the minimum distance of approach reduces background from spurious track crossings.
  • DCAs of the positive and negative daughter tracks to the primary vertex: the daughter tracks are curved due to the magnetic field and a neutral strange particle will decay some distance from the interaction point. Therefore the daughter tracks should not extrapolate back to the primary vertex, but to some distance away from it. Placing a lower limit on this distance can reduce background from tracks originating from the interaction point.
  • V0 decay distance: neutral strange particles decay weakly, with cτ ~ cm, so the decay vertex should typically be displaced from the interaction point. A lower limit placed on the decay distance of the V0 helps eliminate backgrounds from particles originating at the interaction point.

I wrote a class to help perform tuning of these geometrical cut quantities (see /star/u/tpb/StRoot/StV0CutTuning/) by a "brute force" approach; different permutations of the above quantities were attempted, and the resulting mass spectra analysed to see which permutations gave the best balance of background reduction and signal retention. In addition, the consistency of the background to a straight-line shape was required. Due to the limits on statistics, signal retention was considered a greater priority than background reduction. The cut values I decided upon are summarised in table one. Figures one to three show the resulting mass spectra (data are from all runs). Yields are calculated from the integral of bins in the signal (red) region minus the integrals of bins in the background (green) regions. Poisson (√N) errors are used. The background regions are fitted with a straight line, skipping the intervening bins. The signal to background quoted is the ratio of the maximum bin content to the value of the background fit evaluated at that mass. Note that the spectra have the the dE/dx cut included in addition to the geometrical cuts.

Species Max DCA V0 to PV* Max DCA between daughters Min DCA + daughter to PV Min DCA − daughter to PV Min V0 decay distance
K0S 1.0 1.2** 0.5 0.0** 2.0**
Λ 1.5 1.0 0.0** 0.0** 3.0
anti-Λ 2.0** 1.0 0.0** 0.0** 3.0

Table 1: Summary of geometical cuts. All cut values are in centimetres.

* primary vertex
** default cut present in micro-DST


Final K0s invariant mass specturm for all data with all cuts applied
Figure 1: Final K0S mass spectrum with all cuts applied.
Final Lambda invariant mass specturm for all data with all cuts applied
Figure 2: Final Λ mass spectrum with all cuts applied.
Final anti-Lambda invariant mass specturm for all data with all cuts applied
Figure 3: Final anti-Λ mass spectrum with all cuts applied.



Single spin asymmetry using cross formula

Single Spin asymmetry using cross formula

Equation one shows the cross-formula used to calculate the single spin asymmetry.

AP=[sqrt(N(L,up)N(R,down))-sqrt(N(L,down)N(R,up))]/[sqrt(N(L,up)N(R,down))+sqrt(N(L,down)N(R,up))]
Equation 1

where N is a particle yield, L(eft) and R(ight) indicate the side of the polarised beam to which the particle is produced and arrows indicate the polarisation direction of the beam. Equation one cancels acceptance and beam luminosity and allows simply the raw yields to be used for the calculation. The asymmetry can be calculated twice; once for each beam, summing over the polarisation states of the other beam to leave it "unpolarised". I previously used only particles produced at forward η when calculating the blue beam asymmetry, and backward η for yellow, but I now sum over the full η range for each. Equations two and three give the numbers for up/down polarisation for blue (westward at STAR) and yellow (eastward) beams respectively in terms of the contributions from the four different beam polarisation permutations, and these permutations are related to spin bits numbers in table one.


N(blue,up)=N(upUp)+N(downUp),N(blue,down)=N(downDown)+N(upDown)
Equation 2
N(yellow,up)=N(upUp)+N(upDown),N(yellow,down)=N(downDown+N(downUp)
Equation 3

(in e.g. N(upUp), The first arrow refers to yellow beam polarisation, the second to blue beam.)


Beam polarisation 4-bit spin bits
Yellow Blue
Up Up 5
Down Up 6
Up Down 9
Down Down 10
Table 1

The raw asymmetry is calculated for each RHIC fill, then divided by the polarisation for that fill to give the physics asymmetry. Final polarisation numbers (released December 2007) are used. The error on the raw asymmetry is calculated by propagation of the √(N) errors calculated for each particle yield. The final asymmetry error incorporates the polarisation error (statistical and systematic errors summed in quadrature). The fill-by-fill asymmetries for each K0S and Λ for each beam are shown in figures one and two. Anti-Λ results shall be forthcoming. An average asymmetry is calculated by performing a straight line χ2 fit through the fill-by-fill values with ROOT. Table one summarises the asymmetry results. The asymmetry error is the error from the ROOT fit and is statistical only. All fits give a good χ2 per degree of freedom and are consistent with zero within errors.

Fill-by-fill blue beam single spin asymmetry in K0s production
Figure 1a: K0S blue beam asymmetry
Fill-by-fill yellow beam single spin asymmetry in K0s production
Figure 1b: K0S yellow beam asymmetry
Fill-by-fill blue beam single spin asymmetry in Lambda production
Figure 2a: Λ blue beam asymmetry
Fill-by-fill yellow beam single spin asymmetry in Lambda production
Figure 2b: Λ yellow beam asymmetry

The above are summed over the entire pT range available. I also divide the data into different transverse momentum bins and calculate the asymmetry as a function of pT. Figures three and four show the pT-dependent asymmetries. No pT dependence is discernible.

Straight-line fit to pT-dependent K0s cross asymmetry for blue beam
Figure 3a: K0S pT-dependent blue beam AN
Straight-line fit to pT-dependent K0s cross asymmetry for yellow beam
Figure 3b: K0S pT-dependent yellow beam AN
Straight-line fit to pT-dependent Lambda cross asymmetry for blue beam
Figure 4a: Λ pT-dependent blue beam AN
Straight-line fit to pT-dependent Lambda cross asymmetry for yellow beam
Figure 4b: Λ pT-dependent yellow beam AN



Single spin asymmetry utilising relative luminosity

Single spin asymmetry making use of relative luminosity

I also calculate the asymmetry via an alternative method, making use of Tai Sakuma's relative luminosity work. The left-right asymmetry is defined as

Definition of left-right asymmetry
Equation 1

where NL is the particle yield to the left of the polarised beam. The decomposition of the up/down yields into contributions from the four different beam polarisation permutations is the same as given in the cross-asymmetry section (equations 2 and 3). Here, the yields must be scaled by the appropriate relative luminosity, giving the following relations:

Contributions to blue beam counts, scaled for luminosity
Equation 2
Contributions to yellow beam counts, scaled for luminosity
Equation 3

The relative luminosities R4, R5 and R6 are the ratios of luminosity for, respectively, up-up, up-down and down-up bunches to that for down-down bunches. I record the particle yields for each polarisation permutation (i.e. spin bits) on a run-by-run basis, scale each by the appropriate relative luminosity for that run, then combine yields from all the runs in a given fill to give fill-by-fill yields. These are then used to calculate a fill-by-fill raw asymmetry, which is scaled by the beam polarisation. The figures below show the resultant fill-by-fill asymmetry for each beam and particle species, summed over all pT. The fits are again satisfactory, and give asymmetries consistent with zero within errors, as expected.

K0s blue beam asymmetry using relative luminosity
Figure 1a: Blue beam asymmetry for K0S
K0s yellow beam asymmetry using relative luminosity
Figure 1b: Yellow beam asymmetry for K0S
Lambda blue beam asymmetry using relative luminosity
Figure 2a: Blue beam asymmetry for Λ
Lambda yellow beam asymmetry using relative luminosity
Figure 2b: Yellow beam asymmetry for Λ



V0 decays

V0 decays

The appearance of the decay of an unobserved neutral strange particle into two observed charged daughter particles gives rise to the terminology 'V0' to describe the decay topology. The following neutral strange species have been analysed:

Species Decay channel Branching ratio
K0S π+ + π- 0.692
Λ p + π- 0.639
anti-Λ anti-p + π+ 0.639

Candidate V0s are formed by combining together all possible pairs of opposite charge-sign tracks in an event. The invariant mass of the V0 candidate under different decay hypotheses can then be determined from the track momenta and the daughter masses (e.g. for Λ the positive daughter is assumed to be a proton, the negative daughter a π-minus). Raw invariant mass spectra are shown below. The spectra contain three contributions: real particles of the species of interest; neutral strange particles of a different species; combinatorial background from chance positive/negative track crossings.


Invariant mass spectrum for V0 candidates under K0s decay hypothesis
Figure 1: Invariant mass spectrum under K0s hypothesis
Invariant mass spectrum for V0 candidates under Lambda decay hypothesis
Figure 2: Invariant mass spectrum under Λ hypothesis
Invariant mass spectrum for V0 candidates under anti-Lambda decay hypothesis
Figure 3: Invariant mass spectrum under anti-Λ hypothesis

Selection cuts are applied to the candidates to suppress the background whilst maintaining as much signal as possible. There are two methods for reducing background; energy-loss particle identification and geometrical cuts on the V0 candidates.




Photon-jet with the Endcap (Ilya Selyuzhenkov)

Gamma-jets

W-analysis

2008

Year 2008 posts

 

01 Jan

January 2008 posts

 

2008.01.30 Selecting gamma-jet candidates out of the jet trees

Ilya Selyuzhenkov January 30, 2008

Data set

jet trees by Murad Sarsour for pp2006 run, runId=7136022 (~60K events, no triggerId cuts yet)

Jets gross features

  • Figure 1: Distribution of number of jets per event. Same data on a log scale is here.

  • Figure 2: Distribution of electromagnetic energy (EM) fraction, R_EM, for di-jet events (number of jets/event = 2).
    R_EM = [E_t(endcap)+E_t(barrel)]/E_t(total).
    Black histogram is for R_EM1 = max(Ra, Rb), red is for R_EM2 = min(Ra, Rb).
    Ra and Rb are EM fraction for jets in the di-jet event.
    Same data on a log scale is here.

     

Gamma-jet isolation cuts list:

  1. selecting di-jet events with one of the jet dominated by EM energy,
    and another one with more hadronic energy:

    R_EM1 >0.9 and R_EM2 < 0.9

  2. selecting di-jet events with jets pointing opposite in azimuth:

    cos(phi1 - phi2) < -0.9

  3. requiring the number of associated charged tracks with a first jet (with maximum EM fraction) to be less than 2:

    nChargeTracks1 < 2

  4. requiring the number of fired EEMC towers associated with a first jet (with maximum EM fraction) to be 1 or 2:

    0 < nEEMCtowers1 < 3

     

Applying gamma-jet isolation cuts

  • Figure 3: Distribution of eta vs number of EEMC towers for the first jet (with maximum EM fraction).
    Cuts:1-3 applied (no 0 < nEEMCtowers1 < 3 cut).

  • Figure 4: Distribution of transverse momentum, pt1, of the first jet (with maximum EM fraction)
    vs transverse momentum, pt2, of the second jet.
    Cuts:1-4 applied

  • Figure 5: Distribution of mean transverse momentum, < pt1 >, of the first jet (with maximum EM fraction)
    vs transverse momentum, pt2, of the second jet.
    Cuts:1-4 applied

  • Figure 6: Distribution of pseudorapidity, eta1, of the first jet (with maximum EM fraction)
    vs pseudorapidity, eta2, of the second jet.
    Cuts:1-4 applied

  • Figure 7: Distribution of azimuthal angle, phi1, of the first jet (with maximum EM fraction)
    vs azimuthal angle, phi2, of the second jet.
    Cuts:1-4 applied

  • Figure 8: Distribution of transverse momentum, pt1, of the first jet (with maximum EM fraction)
    vs transverse energy sum for the EEMC towers associated with this jet.
    Cuts:1-4 applied

  • Figure 9: Distribution of transverse momentum, pt1, of the first jet (with maximum EM fraction)
    vs transverse momentum, pt2, of the second jet.
    Cuts:1-4 + Et(EEMC) > 3.0 GeV

 

02 Feb

February 2008 posts

 

2008.02.13 Gamma-jet candidates: EEMC response

Ilya Selyuzhenkov February 13, 2008

Data sample

Gamma-jet selection cuts are discussed here. There are 278 candidates found for runId=7136022.
Transverse momentum distribution for the gamma-jet candidates can be found here.

Vertex z distribution for di-jet and gamma-jet events

  • Figure 1: Vertex z distribution.

    Red line presents gamma-jet candidates (scaled by x50). Black is for all di-jet events.
    Same data on a log scale is here.

  • Figure 2: Average vertex z as a function of transverse momentum of the fist jet (with a largest EM energy fraction).
    Red is for gamma-jet candidates. Black is for all di-jet events.
    Strong deviation from zero for gamma-jet candidates at pt < 5GeV?

     

EEMC response for the gamma-jet candidate

EEMC response event by event for all 278 gamma-jet candidate can be found in this pdf file.
Each page shows SMD/Tower energy distribution for a given event:

  1. First row on each page shows SMD response
    for the sector which has a maximum energy deposited in the EEMC Tower
    (u-plane is on the left, v-plane is on the right).

  2. In the left plot (u-plane energy distribution) numerical values for
    pt of the first jet (with maximum EM fraction) and the second jet are given.

  3. In addition, fit results assuming gamma (single Gaussian, red line) or
    neutral pion (double Gaussian, blue line ~ red+green) hypotheses are given.

  4. m_{gamma gamma} value (it is shown in the right plot for v-plane).

    If m_{gamma gamma} value is negative, then the reconstruction procedure has failed
    (for example, no uv-strips intersection found, or tower energy and uv-strips intersection point mismatch, etc).
    EEMC response for these "bad" events can be found in this pdf file.

    If reconstruction procedure succeded, then
    m_{gamma gamma} gives reconstructed invariant mass assuming that two gammas hit the calorimeter.

    Figure 3: invariant mass distribution (assuming pi0 hypothesis).

    Note, that I'm still working on my fitting algorithm (which is not explained here),
    and fit results and the invariant mass distribution will be updated.

     

  5. It is also shown the ratio for each u/v plane
    of the integrated single Gaussian fit (red line) to the total energy in the plane
    (look for "gamma U/V " values on the right v-plane plot).

  6. Second and third rows on each page show the energy deposition in the
    tower, pre-shower1, pre-shower2, and post-shower as a function of eta:phi (etaBin:phiBin).

  7. Last row shows the hit distribution in the SMD for all sectors
    (u-plane on the left, v-plane of the right).

Playing with a different cuts

Trying to isolate the real gammas which hits the calorimeter,
I have sorted events into different subsets based on the following set of cuts:

  1. EEMC gamma-jet cuts (energetic photon hits EEMC with pt similar or greater to that of the opposite jet)

    if (invMass < 0) reject
    if (jet2_pt > jet1_pt) reject
    if (jet1_pt < 7) reject
    if (minFraction < 0.75) reject
    (minFraction = gamma U/V - is a fraction of the integrated single Gaussian peak to the total energy in the uv-plane)

    Figure 4: Sample gamma-jet candidate EEMC response
    (all gamma-jet candidates selected according to these conditions can be found in this pdf file):

  2. EEMC pi0 cuts:

    if (invMass < 0) reject
    if (jet2_pt < jet1_pt) reject
    if (jet2_pt < 7) reject
    if (minFraction < 0.75) reject

    Event by event EEMC response for pi0 (di-jet) candidates
    selected according to these conditions can be found in this pdf file.

 

2008.02.20 Gamma-jet candidates: more statistics from jet-trees

Ilya Selyuzhenkov February 20, 2008

Short summary

After processing all available jet-trees for pp2006 (ppProductionLong),
and applying all "gamma-jet" cuts (which are described below):

  • there are 47K di-jet events selected

  • for pt1>7GeV there are 5,4K gamma-jet candidates (3,7K with an additional cut of pt1>pt2)

  • Figure 1: 2,4K events with both pt1, pt2 > 7GeV

  • 721 candidates within a range of pt1>pt2 and both pt1, pt2 > 7 GeV

Data set

jet trees by Murad Sarsour for pp2006 run, number of runs processed: 323
4.7M di-jet events found (no triggerId cuts yet)

Di-jets gross features

  • Figure 2: Distribution of electromagnetic energy (EM) fraction, R_EM, for di-jet events (number of jets/event = 2).
    R_EM = [E_t(endcap)+E_t(barrel)]/E_t(total).
    Black histogram is for R_EM1 = max(Ra, Rb), red is for R_EM2 = min(Ra, Rb).
    Ra and Rb are EM fraction for jets in the di-jet event.
    Same data on a log scale is here.

     

Gamma-jet isolation cuts:

  1. selecting di-jet events with one of the jet dominated by EM energy,
    and another one with more hadronic energy:

    R_EM1 >0.9 and R_EM2 < 0.9

  2. selecting di-jet events with jets pointing opposite in azimuth:

    cos(phi1 - phi2) < -0.9

  3. requiring the number of associated charged tracks with a first jet (with maximum EM fraction) to be less than 2:

    nChargeTracks1 < 2

  4. requiring the number of fired EEMC towers associated with a first jet (with maximum EM fraction) to be 1 or 2:

    0 < nEEMCtowers1 < 3

     

Applying gamma-jet isolation cuts

  • Figure 3: Distribution of eta vs number of EEMC towers for the first jet (with maximum EM fraction).
    Cuts:1-3 applied (no 0 < nEEMCtowers1 < 3 cut).

  • Figure 4: Distribution of transverse momentum, pt1, of the first jet (with maximum EM fraction)
    vs transverse momentum, pt2, of the second jet.
    Cuts:1-4 applied

  • Figure 5: Distribution of mean transverse momentum, < pt1 >, of the first jet (with maximum EM fraction)
    vs transverse momentum, pt2, of the second jet.
    Cuts:1-4 applied

  • Figure 6: Distribution of pseudorapidity, eta1, of the first jet (with maximum EM fraction)
    vs pseudorapidity, eta2, of the second jet.
    Cuts:1-4 applied

  • Figure 7: Distribution of azimuthal angle, phi1, of the first jet (with maximum EM fraction)
    vs azimuthal angle, phi2, of the second jet.
    Cuts:1-4 applied

  • Figure 8: Distribution of transverse momentum, pt1, of the first jet (with maximum EM fraction)
    vs transverse energy sum for the EEMC towers associated with this jet.
    Cuts:1-4 applied

  • Figure 9: Distribution of transverse momentum, pt1, of the first jet (with maximum EM fraction)
    vs transverse momentum, pt2, of the second jet.
    Cuts:1-4 + Et(EEMC) > 3.0 GeV

 

2008.02.27 Tower based clustering algorithm, and EEMC/BEMC candidates

Ilya Selyuzhenkov February 27, 2008

Gamma-jet candidates before applying clustering algorithm

Gamma-jet isolation cuts:

  1. selecting di-jet events with the first jet dominated by EM energy,
    and the second one with a large fraction of hadronic energy:

    R_EM1 >0.9 and R_EM2 < 0.9

  2. selecting di-jet events with jets pointing opposite in azimuth:

    cos(phi1 - phi2) < -0.8

  3. requiring no charge tracks associated with a first jet (jet with a maximum EM fraction):

    nCharge1 = 0

Figure 1: Transverse momentum

Figure 2: Pseudorapidity

Figure 3: Azimuthal angle

Tower based clustering algorithm

  • for each gamma-jet candidate finding a tower with a maximum energy
    associated with a jet1 (jet with a maximum EM fraction).

  • Calculating energy of the cluster by finding all adjacent towers and adding their energy together.

  • Implementing a cut based on cluster energy fraction, R_cluster, where

    R_cluster is defined as a ratio of the cluster energy
    to the total energy in the calorimeter associated with a jet1.
    Note, that with a cut Ncharge1 =0, energy in the calorimeter is equal to the jet energy.

 

Distribution of cluster energy vs number of towers fired in EEMC/BEMC

Figure 4: R_cluster vs number of towers fired in EEMC (left) and BEMC (right). No pt cuts.

Figure 5: R_cluster vs number of towers fired in EEMC (left) and BEMC (right). Additional cut: pt1>7GeV

Figure 6: jet1 pseudorapidity vs number of towers fired in EEMC (left) and BEMC (right).

 

R_cluster>0.9 cut: EEMC vs BEMC gamma-jet candidates

EEMC candidates: nTowerFiredBEMC=0
BEMC candidates: nTowerFiredEEMC=0

Figure 7: Pseudorapidity (left EEMC, right BEMC candidates)

Figure 8: Azimuthal angle (left EEMC, right BEMC candidates)

Figure 9: Transverse momentum (left EEMC, right BEMC candidates)

 

Number of gamma-jet candidates with an addition pt cuts

Figure 10: Transverse momentum (left EEMC, right BEMC candidates): pt1>7GeV

Figure 11: Transverse momentum (left EEMC, right BEMC candidates): pt1>7 and pt2>7

03 Mar

March 2008 posts

 

2008.03.03 EEMC SMD: u/v-strip energy distribution

Ilya Selyuzhenkov March 03, 2008

Data set: ppLongitudinal, runId = 7136033.

Some observations/questions:

  1. In general distributions look clean and good

  2. Sectors 7 and 9 for v-plane and sector 7 for u-plane are noise.

  3. Sector 9 has a hot strip (id ~ 120)

  4. In sector 3, strips id=0-5 in v-plane are hot (see figure 2 right, bottom)

  5. Sectors 2 and 8 in u-plane and sectors 3 and 9 in v-plane have missing strips id=283-288?

  6. Strips 288 are always empty?

Figure 1:Average energy E in the strip vs sector and strip number (max < E > = 0.0027)
same figure on a log scale

Figure 2: Average energy E for E>0.02 (max < E > = 0.0682)
Same figure on a log scale

2008.03.12 Gamma-jet candidates: 2-gammas invariant mass and Eemc response

Ilya Selyuzhenkov March 12, 2008

Gamma-jet candidates: 2-gammas invariant

Note: Di-jet transverse momentum distribution for these candidates can be found on figure 11 at this page

Figure 1:Invariant mass distribution for gamma-jet candidates assuming pi0 (2-gammas) hypothesys

Figure 2:Invariant mass distribution for gamma-jet candidates assuming pi0 (2-gammas) hypothesys
with an additional SMD isolation cut: gammaFraction >0.75
GammaFraction is defined as ratio of the integral
other SMD strips for the first peak to the total energy in the sector

 

EEMC response for the gamma-jet candidates (gammaFraction >0.75)

  1. pdf file (first 100 events) with event by event EEMC response for the candidates reconstructed into pion mass (gammaFraction >0.75)

  2. pdf file with event by event EEMC response for the candidates not reconstructed into pion mass
    (second peak not found), but has a first peak with gammaFraction >0.75.

 

2008.03.20 Sided residual and chi2 distribution for gamma-jet candidates

Ilya Selyuzhenkov March 20, 2008

Side residual (no pt cut on gamma jet-candidates)

The procedure to discriminate gamma candidate from pions (and other background)
based on the SMD response is described at Pibero's web page.

 

Figure 1: Fit integral vs maximum residual for gamma-jet candidates requesting
no energy deposited in the EEMC pre-shower 1 and 2
(within a 3x3 clusters around tower with a maximum energy).

Black line is defined from MC simulations (see Jason's simulation web page, or Pibero's page above).

 

Figure 2: Fit integral vs maximum residual for gamma-jet candidates requesting requesting
no energy deposited in pre-shower 1 cluster and
no energy deposited in post-shower cluster (this cut is not really essential in demonstrating the main idea)

 

Figure 3: Fit integral vs maximum residual for gamma-jet candidates requesting requesting
non-zero energy deposited in both clusters of pre-shower 1 and 2

 

Side residual: first and second jet pt are greater than 7GeV

Event by event EEMC response for gamma-jet candidates for the case of
no energy deposited in the EEMC pre-shower 1 and 2 can be found in this pdf file

 

Figure 4: Fit integral vs maximum residual for gamma-jet candidates requesting
no energy deposited in the EEMC pre-shower 1 and 2

 

Figure 5: Fit integral vs maximum residual for gamma-jet candidates requesting requesting
no energy deposited in pre-shower 1 cluster and
no energy deposited in post-shower cluster

 

Figure 6: Fit integral vs maximum residual for gamma-jet candidates requesting requesting
non-zero energy deposited in both clusters of pre-shower 1 and 2

 

Chi2 distribution for gamma-jet candidates

Monte Carlo shape

Event Monte Carlo shape allows to distinguish gammas from background by cutting at chi2/ndf < 0.5
(although the distribution looks wider than for the case of Will's shape).

 

Figure 7: Chi2/ndf for gamma-jet candidates using Monte Carlo shape requesting
no energy deposited in both clusters of pre-shower 1 and 2

 

Figure 8: Chi2/ndf for gamma-jet candidates using Monte Carlo shape requesting
non-zero energy deposited in both clusters of pre-shower 1 and 2

 

Will''s shape

Less clear where to cut on chi2?

 

Figure 9: Chi2/ndf for gamma-jet candidates using Monte Carlo shape requesting
no energy deposited in both clusters of pre-shower 1 and 2

 

Figure 10: Chi2/ndf for gamma-jet candidates using Monte Carlo shape requesting
non-zero energy deposited in both clusters of pre-shower 1 and 2 

 

2008.03.26 Sided residual and chi2 distribution for gamma-jet candidates (pre1,2 sorted)

Ilya Selyuzhenkov March 26, 2008

gamma-jet candidates (no pt cut)

Definitions:

  • F_peak - integral for a fit within [-2,2] strips around SMD u/v peak
  • D_peak - integral over the data within [-2,2] strips around SMD u/v peak
  • D_tail^max (D_tail^min) - maximum (minimum) integral over the data tail within +-[3,30] strips from a SMD u/v peak
  • F_tail is the integral over the fit tail within [3,30] strips from a SMD u/v peak.
  • Maximum residual = D_tail^max - F_tail

All results are for combined distributions from u and v planes: ([u]+[v])/2
Gamma-jet isolation cuts described here
Additional quality cuts:

  1. Matching between 3x3 tower cluster and u-v high strip intersection
  2. At least 4 strips fired within [-2,2] strips from a peak

Figure 1: F_peak vs maximum residual
for various cuts on energy deposited in the EEMC pre-shower 1 and 2
(within a 3x3 clusters around tower with a maximum energy).

 

Figure 2: F_data vs D_tail^max
Note:This plot is fit independend (only the peak position is defined based on the fit)

 

Figure 3: F_data vs D_tail^max-D_tail^max

 

Figure 4: Gamma transverse momentum vs jet transverse momentum

 

gamma-jet candidates: pt > 7GeV

Figure 5: F_peak vs maximum residual
for various cuts on energy deposited in the EEMC pre-shower 1 and 2
(within a 3x3 clusters around tower with a maximum energy).

Figure 6: F_data vs D_tail^max
Note:This plot is fit independend (only the peak position is defined based on the fit)

Figure 7: F_data vs D_tail^max-D_tail^max

Figure 8: Gamma transverse momentum vs jet transverse momentum

 

gamma-jet candidates: eta, phi, and max[u,v] strip distributions (no pt cuts)

Figure 9: Gamma pseudorapidity vs jet pseudorapidity

 

Figure 10: Gamma azimuthal angle vs jet azimuthal angle
Note: for the case of Pre1>1 && Pre2==0 there is an enhancement around phi_gamma = 0?

 

Figure 11: maximum strip in v-plane vs maximum strip in u-plane

 

Chi2 distribution for gamma-jet candidates (no pt cuts)

Figure 12:Chi2/ndf for gamma-jet candidates using Monte Carlo shape (combined for [u+v]/2 plane )

Figure 13:Chi2/ndf for gamma-jet candidates (combined for [u+v]/2 plane ) using Will's shape

 

2008.03.28 EEMC SMD shapes: gamma's from gamma-jets (data), MC, and eta-meson analysis

Ilya Selyuzhenkov March 28, 2008

Some observations:

  1. SMD data-driven shapes from different analysis are in a good agreement (Figure 1, upper left plot)
  2. Overall MC shape is too narrow compared to the data shapes (Figure 1, upper left plot)
  3. Shapes are similar with or without gamma-jet 7GeV pt cut (compare Figures 1 and 2),
    what may indicate that shape is independent on energy (at least within our kinematic limits).
  4. Data-driven and MC shapes are getting close to each other (Figure 4, upper left plot)
    when requiring no energy above threshold in both preshower layers and
    with suppressed contribution from pi0 background.
    The latter is achieved by using the information on
    reconstructed invariant mass of 2gamma candidates (compare Figure 3 and 4).

    One interpretation of this can be that in Monte Carlo simulations
    the contribution from the material in front of the detector is underestimated

  5. Energy distribution for each strip in the SMD peak does not looks like a Gaussian (Figure 5),
    what makes very difficult to interpret results obtained from chi2 analysis (Figure 6-8).
  6. Triple Gaussian fit gives a better description of the data shapes,
    compared to the double Gaussian function (compare red and black lines on Figure 1-4)

 

Figure 1: EEMC SMD shape comparison for various preshower cuts
(black points shows u-plane shape only, v-plane results can be found here)

 

Figure 2: EEMC SMD shape comparison for various preshower cuts with gamma-jet pt cut of 7GeV
(black points shows u-plane shape only, v-plane results can be found here)

 

Figure 3: Shapes with an additional cut on 2-gamma candidates within pi0 invariant mass range.
Sample invariant mass distribution using "simple" pi0 finder can be found here
(black points shows u-plane shape only, v-plane results can be found here)

 

Figure 4: Shapes for the candidates when "simple" pi0 finder failed to find a second peak
(black points shows u-plane shape only, v-plane results can be found here)

 

Figure 5: Strip by strip SMD energy distribution.
Only 12 strips from the right side of the maximum are shown.
Zero strip (first upper left plot) corresponds to the high strip in the shape
Note, that already at the 3rd strip from a peak,
RMS values are comparable to those for a mean, and for a higher strips numbers RMS starts to be bigger that mean.
(results for u-plane only, v-plane results can be found here)

 

Comparing chi2 distributions for gamma-jet candidates using MC, Will, and Pibero's shapes

Results for side residual (together with pt, eta, phi distributions) for gamma-jet candidates can be found at this web page

Red histograms on Figures 6-8 shows chi2 distribution from MC-photons (normalized at chi2=1.4)
Blue histograms on Figures 6-8 shows chi2 distribution from MC-pions (normalized at chi2=1.4)

Figure 6: Chi2/ndf for gamma-jet candidates using Monte Carlo shape

 

Figure 7: Chi2/ndf for gamma-jet candidates using Will's shape (derived from eta candidates based on Weihong's pi0-finder)

Figure 8: Chi2/ndf for gamma-jet candidates using Pibero's shape (derived from eta candidates)

 

04 Apr

April 2008 posts

 

2008.04.02 EEMC SMD shapes: data-driven (eta, gamma-jet) vs Monte Carlo (single gamma, gamma-jet)

Ilya Selyuzhenkov April 02, 2008

Some observations:

  1. SMD data-driven shapes from eta-meson and gamma-jet studies
    are in a good agreement for different preshower conditions
    (compage Fig.1 green circles/triangles in upper-left/bottom-right plots)
  2. single gamma MC shapes show preshower dependance,
    but they are still narrower compared to the data shapes
    (compare Fig.1 green circles vs blue open squares)
  3. MC shapes for gamma-jet and single gamma are consistent (Fig.1, bottom right plot)

 

Figure 1: EEMC SMD shape comparison for various preshower cuts
Note:Only MC gamma-jet shape (open red squares) is the same on all plots

2008.04.02 Sided residual: Using data driven gamma-jet shape (3 gaussian fit)

Ilya Selyuzhenkov April 02, 2008

Figure 1: Side residual for various cuts on energy deposited in the EEMC pre-shower 1 and 2
No EEMC SMD based cuts

 

Figure 2: Side residual for various cuts on energy deposited in the EEMC pre-shower 1 and 2
"Simple" pi0 finder can not find a second peak

 

Figure 3: Side residual for various cuts on energy deposited in the EEMC pre-shower 1 and 2
"Simple" pi0 finder reconstruct the invarian mass within [0.1,0.18] range

 

Figure 4: Side residual distribution (Projection for side residual in Figs.1-3 on vertical axis)

 

Figure 5: Signal (green: m < 0) vs background (black, red) separation

2008.04.02 Sided residual: single gamma Monte-Carlo simulations

Ilya Selyuzhenkov April 02, 2008

Side residual: single gamma Monte-Carlo simulations

Figure 1: Side residual for various cuts on energy deposited in the EEMC pre-shower 1 and 2
No EEMC SMD based cuts

2008.04.03 chi2-shape subtraction for different Preshower conditions

Ilya Selyuzhenkov April 03, 2008

Request from Hal Spinka:

Hi Ilya,

I think you gave up on the chi-squared method too quickly, and am sorry I missed the phone meeting last week. So, I would like to make a request that will hopefully take a minimal amount of your time to show that all is okay. Then, if there is a delay in getting the sided residual information out and into the beam use request, you can still fall back on the chi-squared method.

In your March 28 posting, Figure 8 at the bottom, I would like to get numerical values for the events per bin for the black curves. I won't use the preshower1>0 and preshower2=0 data, so those you don't need to send. Also, I won't use the red or blue curve information.

I think your problem has been that you normalized your curves at chi-squared/ndf = 1.4 instead of the peak. What I plan to do is to normalize the (pre1=0, pre2=0) to the (pre1=0, pre2>0) data in the peak and subtract. The (pre1=0, pre2=0) set should have some single photons, but also some multiple photons. The (pre1=0, pre2>0) should also have single photons, and more multiple photons, since the chance that one of them will convert is larger. The difference should look roughly like your blue curve, though perhaps not exactly if Pibero's mean shower shape is not perfect (which it isn't). I will do the same thing with taking the difference between (pre1>0, pre2>0) and (pre1=0, pre2=0), and again the difference should look roughly like your blue curve. The (pre1>0, pre2>0) data should have even larger fraction of multiple photons than either of the other two data sets. I would expect the two difference curves to look approximately the same.

Hope this is possible for you to do. Since our reduced chi-squared curve looks so much like the one from CDF, I am pretty confident that we are okay, but this should be checked to convince people that we are not doing anything terribly wrong.

Reply by Ilya:

Dear Hal,

I have tried to implement your idea and produce a figure attached.

There are 4 plots in it:

1. Upper left plot shows normalized to unity (at maximum) chi2 distribution (obtained with Pibero shape for gamma-jet candidates) for a different pre1, pre2 conditions

2. Upper right plot shows bin-by-bin difference: a) between normalized chi2 for pre1=0, pre2>0 and pre1=0, pre2=0 (red) and b) between normalized chi2 for pre1>0, pre2>0 and pre1=0, pre2=0 (blue)

3. Bottom left Same as upper right, but normalization were done based on the integral within [-4,4] bins around maximum.

4. Bottom right Same as for upper right, but with a different normalization ([-4,4] bins around maximum)

I have also tried to normalized by the total integral, but the results looks similar.

 

Figure 1: See description above

 

Figure 2: Same without log scale (See description above)

2008.04.09 Applying gamma-jet reconstruction algorithm for gamma-jet simulated events

Ilya Selyuzhenkov April 09, 2008

Data sample:
Monte-Carlo gamma-jet sample for partonic pt range of 5-7, 7-9, 9-11,11-15, 15-25, 25-35 GeV.

Analysis: Simulated MuDst files were first processed through jet finder algorithm (thanks to Renee Fatemi),
and later analyzed by applying gamma-jet isolation cuts (see this link for details) and studying EEMC SMD response (see below).
To test the algorithm, Geant records were not used in this analysis.
Further studies based on Geant records (yield estimates, etc) are ongoing.

EESMD shapes comparison

Figure 1:Comparison between shower shape profile for data and MC.
Black circles shows results for MC gamma-jet sample (all partonic pt).
For v-plane results see this figure

 

Correlation between gamma and jet pt, eta, phi

Figure 2:Gamma vs jet transverse momentum.

 

Figure 3:Gamma vs jet azimuthal angle.

 

Figure 4:Gamma vs jet pseudo-rapidity.

 

Results from maximum sided residua study

Definitions for F_peak, D_peak, D_tail^max (D_tail^min) can be found here

Figure 5:F_peak vs maximum residual
for various cuts on energy deposited in the EEMC pre-shower 1 and 2
(within a 3x3 clusters around tower with a maximum energy).
Shower shape used to fit data is fixed to the shape from the previous gamma-jet study of real events
(see black point on Fig.1 [upper left plot] at this page)

 

Figure 6: F_peak vs D_tail^max: click here
Figure 7: F_peak vs D_tail^max-D_tail^min: click here

Postshower to SMD[uv] energy ratio

Figure 8:Logarithmic fraction of energy in post shower (3x3 cluster) to the total energy in SMD u- and v-planes

 

Figure 8a:
Same as figure 8, but for gamma-jet candidates from the real data (no pt cuts).
Logarithmic fraction of energy in post shower (3x3 cluster) to the total energy in SMD u- and v-planes

 

Figure 8b:
Comparison between gamma-jet candidates from data with different preshower conditions.
Points are normalized in peak to the case of pre1 > 0, pre2 > 0

Logarithmic fraction of energy in post shower (3x3 cluster) to the total energy in SMD u- and v-planes

 

Figure 8c:
Comparison between gamma-jet candidates from Monte-Carlo simulations with different preshower conditions.
Points are normalized in peak to the case of pre1 > 0, pre2 > 0

Logarithmic fraction of energy in post shower (3x3 cluster) to the total energy in SMD u- and v-planes

 

Additional QA plots

Figure 9: Jet neutral energy fraction
Figure 10: High v-strip vs u-strip
Figure 11: energy post shower (3x3 cluster)
Figure 12: Peak energy SMD-u
Figure 13: Peak energy SMD-v
Figure 14: Gamma phi
Figure 15: Gamma pt
Figure 16: Gamma eta
Figure 17: Delta gamma-jet pt
Figure 18: Delta gamma-jet eta
Figure 19: Delta gamma-jet phi

 

chi2 distributions

Figure 20:chi2 distribution using "standard" MC shape

 

Figure 21:chi2 distribution using Pibero shape

2008.04.16 Sided residual: Data Driven MC vs raw MC vs 2006 data

Ilya Selyuzhenkov April 16, 2008

Figure 1: Sided residual for raw MC (partonic pt 9-11)

 

Figure 2: Sided residual for data-driven MC (partonic pt 9-11)

 

Figure 3: Sided residual for data (pp Longitudinal 2006)

 

Different analysis cuts vs number of events which passed the cut

  1. N_events : total number of di-jet events found by the jet-finder for gamma in eta region [1,2]
    (Geant record is used to get this number)
  2. cos(phi_gamma - phi_jet) < -0.8 : gamma-jet opposite in phi
  3. R_{3x3cluster} > 0.9 : Energy in 3x3 cluster of EEMC tower to the total jet energy.
  4. R_EM^jet < 0.9 : neutral energy fraction cut for on away side jet
  5. N_ch=0 : no charge tracks associated with a gamma candidate
  6. N_bTow = 0 : no barrel towers associated with a gamma candidate (gamma in the endcap)
  7. N_(5-strip clusler)^u > 3 : minimum number of strips in EEMC SMD u-plane cluster around peak
  8. N_(5-strip cluster)^v > 3 : minimum number of strips in EEMC SMD v-plane cluster around peak
  9. gamma-algo fail : my algorithm failed to match tower with SMD uv-intersection, etc...
  10. Tow:SMD match : SMD uv-intersection has a tower which is not in a 3x3 cluser

Figure 4: Number of events which passed various cuts (MC data, partonic pt 9-11)

 

2008.04.17 Sided residual: Data Driven MC vs raw MC (partonic pt=5-35) vs 2006 data

Ilya Selyuzhenkov April 17, 2008

MC data for different pt weigted according to Michael Betancourt web page:
weight = xSection[ptBin] / xSection[max] / nFiles

Figure 1: Sided residual for raw MC (partonic pt 5-35)
(same plot for partonic pt 9-11)

 

Figure 2: Sided residual for data-driven MC (partonic pt 5-35)
(same plot for partonic pt 9-11)

 

Figure 3: Sided residual for data (pp Longitudinal 2006)

 

Figure 4: Sided residual for data (pp Longitudinal 2006)

 

Figure 5: Sided residual for data (pp Longitudinal 2006)

 

Figure 6: pt(gamma) from geant record vs
pt(gamma) from energy in 3x3 tower cluster and position for uv-intersection wrt vertex
(same on a linear scale)

 

Figure 7: pt(gamma) from geant record vs
pt(jet) as found by the jet-finder

 

Figure 8: gamma pt distribution:
data-driven MC (red) vs gamma-jet candidates from pp2006 longitudinal run (black).
MC distribution normalized to data at maximum for each preshower condition

 

Different analysis cuts vs number of events which passed the cut

  1. N_events : total number of di-jet events found by the jet-finder for gamma in eta region [1,2]
    (Geant record is used to get this number)
  2. cos(phi_gamma - phi_jet) < -0.8 : gamma-jet opposite in phi
  3. R_{3x3cluster} > 0.9 : Energy in 3x3 cluster of EEMC tower to the total jet energy.
  4. R_EM^jet < 0.9 : neutral energy fraction cut for on away side jet
  5. N_ch=0 : no charge tracks associated with a gamma candidate
  6. N_bTow = 0 : no barrel towers associated with a gamma candidate (gamma in the endcap)
  7. N_(5-strip clusler)^u > 3 : minimum number of strips in EEMC SMD u-plane cluster around peak
  8. N_(5-strip cluster)^v > 3 : minimum number of strips in EEMC SMD v-plane cluster around peak
  9. gamma-algo fail : my algorithm failed to match tower with SMD uv-intersection, etc...
  10. Tow:SMD match : SMD uv-intersection has a tower which is not in a 3x3 cluser

Figure 9: Number of events which passed various cuts (MC data, partonic pt 5-35)
Red: cuts applied independent
Black: cuts applied sequential from left to right

 

2008.04.23 Gamma-jet candidates: pp2006 data vs data-driven MC (gamma-jet and bg:jet-jet)

Ilya Selyuzhenkov April 23, 2008

Sided residual: pp2006 data vs data-driven MC (gamma-jet and bg:jet-jet)

MC data for different partonic pt are weigted according to Michael Betancourt web page:
weight = xSection[ptBin] / xSection[max] / nFiles

Figure 1:Sided residual for data-driven gamma-jet MC events (partonic pt 5-35)

 

Figure 2:Sided residual for data-driven jet-jet MC events (partonic pt 3-55)

 

Figure 3:Sided residual for data (pp Longitudinal 2006)

 

Figure 4:pt(gamma) vs pt(jet) for data-driven gamma-jet MC events (partonic pt 5-35)

 

Figure 5:pt(gamma) vs pt(jet) for data-driven jet-jet MC events (partonic pt 3-55)

 

Figure 6:pt(gamma) vs pt(jet) for data (pp Longitudinal 2006)

05 May

May 2008 posts

 

2008.05.05 pt-distributions, sided residual (data vs dd-MC g-jet and bg di-jet)

Ilya Selyuzhenkov May 05, 2008

Data samples:

  • pp2006(long) - 2006 pp production longitudinal data after applying gamma-jet aisolation cuts
    (jet-tree sample: 4.114pb^-1 from Jamie script, 3.164 pb^1 analyses).
  • gamma-jet - Pythia gamma-jet sample (~170K events). Partonic pt range 5-35 GeV
  • bg jets - Pythia di-jet sample (~4M events). Partonic pt range 3-65 GeV

Figure 1:pt distribution. MC data are scaled to the same luminosity as data
(Normalization factor: Luminosity * sigma / N_events).

 

 

Figure 2:Integrated gamma yield vs pt.
For each pt bin yield is defined as the integral from this pt up to the maximum available pt.
MC data are scaled to the same luminosity as data.

 

Figure 3:Signal to background ratio (all results divided by the data)

 

Sided residual: pp2006 data vs data-driven MC (gamma-jet and bg:jet-jet)

You can find sided residual 2-D plots here

Figure 4:Maximum sided residual for pt_gamma>7GeV; pt_jet>7GeV

 

Figure 5:Fitted peak for pt_gamma>7GeV; pt_jet>7GeV

 

Figure 6:Max data tail for pt_gamma>7GeV; pt_jet>7GeV

 

Figure 7:Max minus min data tails for pt_gamma>7GeV; pt_jet>7GeV

 

Figure 8:Shower shapes pt_gamma>7GeV; pt_jet>7GeV

2008.05.08 y:x EEMC position for gamma-jet candidates

Ilya Selyuzhenkov May 08, 2008

y:x EEMC position for gamma-jet candidates

Figure 1:y:x EEMC position for gamma-jet candidates:
Pythia gamma-jet sample (~170K events). Partonic pt range 5-35 GeV.

 

Figure 2:y:x EEMC position for gamma-jet candidates:
Pythia QCD bg sample (~4M events). Partonic pt range 3-65 GeV.

 

Figure 3:y:x EEMC position for gamma-jet candidates:
pp2006 (long) data [eemc-http-mb-l2gamma:137641 trigger]

 

Figure 3b:y:x EEMC position for gamma-jet candidates:
pp2006 (long) data [eemc-http-mb-l2gamma:137641 trigger]
pt cut of 7 GeV for gamma and 5GeV for the away side jet has been applied.

high u vs. v strip for gamma-jet candidates

 

Figure 4:High v-strip vs high u-strip.
Pythia gamma-jet sample (~170K events). Partonic pt range 5-35 GeV.

Figure 5:High v-strip vs high u-strip:
Pythia QCD bg sample (~4M events). Partonic pt range 3-65 GeV.

 

Figure 6:High v-strip vs high u-strip:
pp2006 (long) data [eemc-http-mb-l2gamma:137641 trigger]

 

Figure 6b:High v-strip vs high u-strip:
pp2006 (long) data [eemc-http-mb-l2gamma:137641 trigger]
pt cut of 7 GeV for gamma and 5GeV for the away side jet has been applied.

 

2008.05.09 Gamma-jet candidates pt-distributions and TPC tracking

Ilya Selyuzhenkov May 09, 2008

Detector eta cut study (1< eta < 1.4):

Figure 1:Gamma pt distribution. MC data are scaled to the same luminosity as data
(Normalization factor: Luminosity * sigma / N_events).

 

Figure 2:Gamma yield vs pt. MC data are scaled to the same luminosity as data.

 

Figure 3:Signal to background ratio (MC results are normalized to the data)

2008.05.14 Gamma-cluster to jet energy ratio and away side jet pt matching

Ilya Selyuzhenkov May 14, 2008

Gamma-cluster to jet1 energy ratio

  • Correlation between gamma-candidate 3x3 cluster energy ratio (R_cluster) and
    number of EEMC towers in a jet1 can be found here (Fig. 4).

  • Gamma pt distribution, yield and signal to background ratio plots
    for a cut of R_cluster >0.9 can be found here (Figs. 1-3).

  • Gamma pt distribution, yield and signal to background ratio plots
    for a cut of R_cluster >0.99 are shown below in Figs. 1-3.
    One can see that by going from R_cluster>0.9 to R_cluster>0.99
    improves signal to background ratio from ~ 1:10 to ~ 1:5 for gamma pt>10 GeV

Figure 1:Gamma pt distribution for R_cluster >0.99.
MC results scaled to the same luminosity as data
(Normalization factor: Luminosity * sigma / N_events).

 

Figure 2:Integrated gamma yield vs pt for R_cluster >0.99
For each pt bin yield is defined as the integral from this pt up to the maximum available pt.
MC results scaled to the same luminosity as data.

 

Figure 3:Signal to background ratio for R_cluster >0.99 (all results divided by the data)
Compare this figure with that for R_cluster>0.9 (Fig. 3 at this link)

 

Gamma and the away side jet pt matching

Figure 4: pt asymmetry between gamma and the away side jet (R_cluster >0.9)
for a three data samples (pp2006[long] data, gamma-jet MC, QCD jets background).
pt cut of 7 GeV for both gamma and jet has been applied.

Figure 5: signal to background ratio (R_cluster >0.9)
as a function of pt asymmetry between gamma and the away side jet
pt cut of 7 GeV for both gamma and jet has been applied.

 

 

Figure 6: pt asymmetry between gamma and the away side jet (R_cluster >0.99)
for a three data samples (pp2006[long] data, gamma-jet MC, QCD jets background).
pt cut of 7 GeV for both gamma and jet has been applied.

Figure 7: signal to background ratio
as a functio of pt asymmetry between gamma and the away side jet (R_cluster >0.99)
pt cut of 7 GeV for both gamma and jet has been applied.

 

 

Figure 8: pt asymmetry between gamma and the away side jet (R_cluster >0.99)
for a three data samples (pp2006[long] data, gamma-jet MC, QCD jets background).
pt cut of 7 GeV for gamma and 5GeV for the away side jet has been applied.

Figure 9: signal to background ratio
as a function of pt asymmetry between gamma and the away side jet (R_cluster >0.99)
pt cut of 7 GeV for gamma and 5GeV for the away side jet has been applied.

 

2008.05.15 Vertex z distribution for pp2006 data, MC gamma-jet and QCD jets events

Ilya Selyuzhenkov May 15, 2008

Figure 1:Vertex z distribution for pp2006 (long) data [eemc-http-mb-l2gamma:137641 trigger]
Note: In the upper right plot (pre1=0, pre2>0) one can see
a hole in the acceptance in the range bweeeen z_vertex -10 to 30 cm (probably due to SVT construction)

 

Figure 1b:Vertex z distribution for pp2006 (same as Fig. 1, but on a linear scale)

 

Figure 2:Vertex z distribution for three different data samples
MC results scaled to the same luminosity as data

 

Figure 3:Vertex z distribution for three different data samples
pt cut of 7 GeV for gamma and 5GeV for the away side jet has been applied.

2008.05.20 Shower shapes sorted by pre-shower, z-vertex and gamma's eta, phi, pt

Ilya Selyuzhenkov May 20, 2008

Gamma-jet algorithm and isolation cuts:

  1. Selecting only di-jet events identified by the STAR jet finder algorithm,
    with jets pointing opposite in azimuth:
    cos(phi_jet1 - phi_jet2) < -0.8

  2. Select jet1 with a maximum neutral energy fraction (R_EM1).
    This is our gamma candidate, for which we further require:
    • No charge tracks associated with jet1 (default jet radius is 0.7):
      nChargeTracks_jet1 = 0
      Note, that this charge track veto only works
      in the EEMC region where we do have TPC tracking
    • No barrel towers associated with jet1 (pure EEMC jet):
      nBarrelTowers_jet1 = 0
    • Ratio of the energy in the 3x3 EEMC high tower cluster
      to the total je